mirror of https://github.com/apache/druid.git
Web console: use new sampler features (#14017)
* use new sampler features * supprot kafka format * update DQT, fix tests * prefer non numeric formats * fix input format step * boost SQL data loader * delete dimension in auto discover mode * inline example specs * feedback updates * yeet the format into valueFormat when switching to kafka * kafka format is now a toggle * even better form layout * rename
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@ -38,6 +38,7 @@ This topic covers how to submit a supervisor spec to ingest event data, also kno
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- For a walk-through, see the [Loading from Apache Kafka](../../tutorials/tutorial-kafka.md) tutorial.
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## Kafka support
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The Kafka indexing service supports transactional topics introduced in Kafka 0.11.x by default. The consumer for Kafka indexing service is incompatible with older Kafka brokers. If you are using an older version, refer to the [Kafka upgrade guide](https://kafka.apache.org/documentation/#upgrade).
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Additionally, you can set `isolation.level` to `read_uncommitted` in `consumerProperties` if either:
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@ -51,6 +52,7 @@ If your Kafka cluster enables consumer-group based ACLs, you can set `group.id`
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To use the Kafka indexing service, load the `druid-kafka-indexing-service` extension on both the Overlord and the MiddleManagers. See [Loading extensions](../extensions.md#loading-extensions) for instructions on how to configure extensions.
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## Define a supervisor spec
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Similar to the ingestion spec for batch ingestion, the supervisor spec configures the data ingestion for Kafka streaming ingestion. A supervisor spec has the following sections:
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- `dataSchema` to specify the Druid datasource name, primary timestamp, dimensions, metrics, transforms, and any necessary filters.
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- `ioConfig` to configure Kafka connection settings and configure how Druid parses the data. Kafka-specific connection details go in the `consumerProperties`. The `ioConfig` is also where you define the input format (`inputFormat`) of your Kafka data. For supported formats for Kafka and information on how to configure the input format, see [Data formats](../../ingestion/data-formats.md).
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@ -128,6 +130,7 @@ The following example demonstrates a supervisor spec for Kafka that uses the `JS
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```
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### Kafka input format supervisor spec example
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If you want to ingest data from other fields in addition to the Kafka message contents, you can use the `kafka` input format. The `kafka` input format lets you ingest:
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- the event key field
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- event headers
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@ -141,7 +144,7 @@ For example, consider the following structure for a message that represents a fi
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- **Event timestamp**: "Nov. 10, 2021 at 14:06"
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When you use the `kafka` input format, you configure the way that Druid names the dimensions created from the Kafka message:
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- `headerLabelPrefix`: Supply a prefix to the Kafka headers to avoid any conflicts with named dimensions. The default is `kafka.header`. Considering the header from the example, Druid maps the header to the following column: `kafka.header.environment`.
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- `headerColumnPrefix`: Supply a prefix to the Kafka headers to avoid any conflicts with named dimensions. The default is `kafka.header`. Considering the header from the example, Druid maps the header to the following column: `kafka.header.environment`.
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- `timestampColumnName`: Supply a custom name for the Kafka timestamp in the Druid schema to avoid conflicts with other time columns. The default is `kafka.timestamp`.
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- `keyColumnName`: Supply the name for the Kafka key column in Druid. The default is `kafka.key`.
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Additionally, you must provide information about how Druid should parse the data in the Kafka message:
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@ -159,7 +162,7 @@ Additionally, you must provide information about how Druid should parse the data
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For more information on data formats, see [Data formats](../../ingestion/data-formats.md).
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Finally, add the Kafka message columns to the `dimensionsSpec`. For the key and timestamp, you can use the dimension names you defined for `keyColumnName` and `timestampColumnName`. For header dimensions, append the header key to the `headerLabelPrefix`. For example `kafka.header.environment`.
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Finally, add the Kafka message columns to the `dimensionsSpec`. For the key and timestamp, you can use the dimension names you defined for `keyColumnName` and `timestampColumnName`. For header dimensions, append the header key to the `headerColumnPrefix`. For example `kafka.header.environment`.
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The following supervisor spec demonstrates how to ingest the Kafka header, key, and timestamp into Druid dimensions:
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```
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@ -174,7 +177,7 @@ The following supervisor spec demonstrates how to ingest the Kafka header, key,
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"topic": "wiki-edits",
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"inputFormat": {
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"type": "kafka",
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"headerLabelPrefix": "kafka.header.",
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"headerColumnPrefix": "kafka.header.",
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"timestampColumnName": "kafka.timestamp",
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"keyColumnName": "kafka.key",
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"headerFormat": {
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@ -170,7 +170,7 @@ Configure the Kafka `inputFormat` to load complete kafka records including heade
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| Field | Type | Description | Required |
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|-------|------|-------------|----------|
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| `type` | String | Set value to `kafka`. | yes |
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| `headerLabelPrefix` | String | Custom label prefix for all the header columns. | no (default = "kafka.header.") |
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| `headerColumnPrefix` | String | Custom prefix for all the header columns. | no (default = "kafka.header.") |
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| `timestampColumnName` | String | Name of the column for the kafka record's timestamp.| no (default = "kafka.timestamp") |
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| `keyColumnName` | String | Name of the column for the kafka record's key.| no (default = "kafka.key") |
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| `headerFormat` | Object | `headerFormat` specifies how to parse the Kafka headers. Supports String types. Because Kafka header values are bytes, the parser decodes them as UTF-8 encoded strings. To change this behavior, implement your own parser based on the encoding style. Change the 'encoding' type in `KafkaStringHeaderFormat` to match your custom implementation. | no |
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@ -183,7 +183,7 @@ For example:
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"ioConfig": {
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"inputFormat": {
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"type": "kafka",
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"headerLabelPrefix": "kafka.header.",
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"headerColumnPrefix": "kafka.header.",
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"timestampColumnName": "kafka.timestamp",
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"keyColumnName": "kafka.key",
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"headerFormat":
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|
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@ -5733,7 +5733,7 @@ license_category: binary
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module: web-console
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license_name: Apache License version 2.0
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copyright: Imply Data
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version: 0.18.2
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version: 0.18.3
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---
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@ -116,7 +116,7 @@ function validateConnectLocalData(preview: string) {
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expect(lines.length).toBe(500);
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const firstLine = lines[0];
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expect(firstLine).toBe(
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'Druid row: {' +
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'[Druid row: {' +
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'"__time":1442018818771' +
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',"channel":"#en.wikipedia"' +
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',"comment":"added project"' +
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@ -131,11 +131,11 @@ function validateConnectLocalData(preview: string) {
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',"added":36' +
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',"deleted":0' +
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',"delta":36' +
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'}',
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'}]',
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);
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const lastLine = lines[lines.length - 1];
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expect(lastLine).toBe(
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'Druid row: {' +
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'[Druid row: {' +
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'"__time":1442020314823' +
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',"channel":"#en.wikipedia"' +
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',"comment":"/* History */[[WP:AWB/T|Typo fixing]], [[WP:AWB/T|typo(s) fixed]]: nothern → northern using [[Project:AWB|AWB]]"' +
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@ -150,7 +150,7 @@ function validateConnectLocalData(preview: string) {
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',"added":1' +
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',"deleted":0' +
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',"delta":1' +
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'}',
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'}]',
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);
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}
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@ -22,7 +22,7 @@
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"d3-axis": "^2.1.0",
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"d3-scale": "^3.3.0",
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"d3-selection": "^2.0.0",
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"druid-query-toolkit": "^0.18.2",
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"druid-query-toolkit": "^0.18.3",
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"file-saver": "^2.0.2",
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"follow-redirects": "^1.14.7",
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"fontsource-open-sans": "^3.0.9",
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@ -8211,9 +8211,9 @@
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}
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},
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"node_modules/druid-query-toolkit": {
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"version": "0.18.2",
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"resolved": "https://registry.npmjs.org/druid-query-toolkit/-/druid-query-toolkit-0.18.2.tgz",
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"integrity": "sha512-MUqTm6wW+clI0pVeK9RIdB8svWK6mu44zsAw8BSVZYYKchigbBzTgwJe0vAYFBfR0TPjD1gJl62pSw4g0F14fQ==",
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"version": "0.18.3",
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"resolved": "https://registry.npmjs.org/druid-query-toolkit/-/druid-query-toolkit-0.18.3.tgz",
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"integrity": "sha512-Za2U2NsFyun5HXeWnLCICnTFzZp4aC17aSOjgVbQgEWZNMPht51U4paE3SVhPDObkWDjDUYAqVv+mO+ZyMx9Og==",
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"dependencies": {
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"tslib": "^2.3.1"
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},
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@ -32625,9 +32625,9 @@
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}
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},
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"druid-query-toolkit": {
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"version": "0.18.2",
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"resolved": "https://registry.npmjs.org/druid-query-toolkit/-/druid-query-toolkit-0.18.2.tgz",
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"integrity": "sha512-MUqTm6wW+clI0pVeK9RIdB8svWK6mu44zsAw8BSVZYYKchigbBzTgwJe0vAYFBfR0TPjD1gJl62pSw4g0F14fQ==",
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"version": "0.18.3",
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"resolved": "https://registry.npmjs.org/druid-query-toolkit/-/druid-query-toolkit-0.18.3.tgz",
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"integrity": "sha512-Za2U2NsFyun5HXeWnLCICnTFzZp4aC17aSOjgVbQgEWZNMPht51U4paE3SVhPDObkWDjDUYAqVv+mO+ZyMx9Og==",
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"requires": {
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"tslib": "^2.3.1"
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}
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@ -76,7 +76,7 @@
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"d3-axis": "^2.1.0",
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"d3-scale": "^3.3.0",
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"d3-selection": "^2.0.0",
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"druid-query-toolkit": "^0.18.2",
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"druid-query-toolkit": "^0.18.3",
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"file-saver": "^2.0.2",
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"follow-redirects": "^1.14.7",
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"fontsource-open-sans": "^3.0.9",
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@ -23,7 +23,7 @@ const snarkdown = require('snarkdown');
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const writefile = 'lib/sql-docs.js';
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const MINIMUM_EXPECTED_NUMBER_OF_FUNCTIONS = 164;
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const MINIMUM_EXPECTED_NUMBER_OF_FUNCTIONS = 167;
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const MINIMUM_EXPECTED_NUMBER_OF_DATA_TYPES = 14;
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const initialFunctionDocs = {
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@ -70,7 +70,7 @@ export interface Field<M> {
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hide?: Functor<M, boolean>;
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hideInMore?: Functor<M, boolean>;
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valueAdjustment?: (value: any) => any;
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adjustment?: (model: Partial<M>) => Partial<M>;
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adjustment?: (model: Partial<M>, oldModel: Partial<M>) => Partial<M>;
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issueWithValue?: (value: any) => string | undefined;
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customSummary?: (v: any) => string;
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@ -217,7 +217,7 @@ export class AutoForm<T extends Record<string, any>> extends React.PureComponent
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}
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if (field.adjustment) {
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newModel = field.adjustment(newModel);
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newModel = field.adjustment(newModel, model);
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}
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this.modelChange(newModel);
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@ -45,7 +45,6 @@ import {
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import './console-application.scss';
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export interface ConsoleApplicationProps {
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exampleManifestsUrl?: string;
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defaultQueryContext?: Record<string, any>;
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mandatoryQueryContext?: Record<string, any>;
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}
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@ -213,15 +212,12 @@ export class ConsoleApplication extends React.PureComponent<
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};
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private readonly wrappedDataLoaderView = () => {
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const { exampleManifestsUrl } = this.props;
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return this.wrapInViewContainer(
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'data-loader',
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<LoadDataView
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mode="all"
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initTaskId={this.taskId}
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initSupervisorId={this.supervisorId}
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exampleManifestsUrl={exampleManifestsUrl}
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goToIngestion={this.goToIngestionWithTaskGroupId}
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/>,
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'narrow-pad',
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@ -241,14 +237,11 @@ export class ConsoleApplication extends React.PureComponent<
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};
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private readonly wrappedClassicBatchDataLoaderView = () => {
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const { exampleManifestsUrl } = this.props;
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return this.wrapInViewContainer(
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'classic-batch-data-loader',
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<LoadDataView
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mode="batch"
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initTaskId={this.taskId}
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exampleManifestsUrl={exampleManifestsUrl}
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goToIngestion={this.goToIngestionWithTaskGroupId}
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/>,
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'narrow-pad',
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|
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@ -1,85 +0,0 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
|
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* distributed under the License is distributed on an "AS IS" BASIS,
|
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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import { CSV_SAMPLE, JSON_SAMPLE } from '../../utils/sampler.mock';
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import { getDimensionSpecs } from './dimension-spec';
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describe('dimension-spec', () => {
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describe('getDimensionSpecs', () => {
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it('works for empty', () => {
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expect(getDimensionSpecs({ header: ['header'], rows: [] }, {}, false, true)).toEqual([
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'header',
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]);
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});
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it('works with json', () => {
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expect(getDimensionSpecs(JSON_SAMPLE, {}, false, false)).toEqual([
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'timestamp',
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'user',
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{
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name: 'followers',
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type: 'long',
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},
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{
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name: 'spend',
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type: 'double',
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},
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'id',
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'tags',
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'nums',
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]);
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expect(getDimensionSpecs(JSON_SAMPLE, {}, false, true)).toEqual([
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'timestamp',
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'user',
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'id',
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'tags',
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'nums',
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]);
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});
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it('works with csv', () => {
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expect(getDimensionSpecs(CSV_SAMPLE, {}, true, false)).toEqual([
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'timestamp',
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'user',
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{
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name: 'followers',
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type: 'long',
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},
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{
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name: 'spend',
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type: 'double',
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},
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{
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name: 'id',
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type: 'long',
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},
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'tags',
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'nums',
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]);
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expect(getDimensionSpecs(CSV_SAMPLE, {}, true, true)).toEqual([
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'timestamp',
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'user',
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'tags',
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'nums',
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]);
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});
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});
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});
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@ -18,13 +18,16 @@
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import type { Field } from '../../components';
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import { filterMap, typeIs } from '../../utils';
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import type { SampleHeaderAndRows } from '../../utils/sampler';
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import { guessColumnTypeFromHeaderAndRows } from '../ingestion-spec/ingestion-spec';
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import type { SampleResponse } from '../../utils/sampler';
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import { getHeaderNamesFromSampleResponse } from '../../utils/sampler';
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import { guessColumnTypeFromSampleResponse } from '../ingestion-spec/ingestion-spec';
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export interface DimensionsSpec {
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readonly dimensions?: (string | DimensionSpec)[];
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readonly dimensionExclusions?: string[];
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readonly spatialDimensions?: any[];
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readonly includeAllDimensions?: boolean;
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readonly useSchemaDiscovery?: boolean;
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}
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export interface DimensionSpec {
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|
@ -77,20 +80,19 @@ export function inflateDimensionSpec(dimensionSpec: string | DimensionSpec): Dim
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}
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export function getDimensionSpecs(
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headerAndRows: SampleHeaderAndRows,
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sampleResponse: SampleResponse,
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typeHints: Record<string, string>,
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guessNumericStringsAsNumbers: boolean,
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hasRollup: boolean,
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): (string | DimensionSpec)[] {
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return filterMap(headerAndRows.header, h => {
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if (h === '__time') return;
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const type =
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return filterMap(getHeaderNamesFromSampleResponse(sampleResponse, true), h => {
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const dimensionType =
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typeHints[h] ||
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guessColumnTypeFromHeaderAndRows(headerAndRows, h, guessNumericStringsAsNumbers);
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if (type === 'string') return h;
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guessColumnTypeFromSampleResponse(sampleResponse, h, guessNumericStringsAsNumbers);
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if (dimensionType === 'string') return h;
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if (hasRollup) return;
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return {
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type,
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type: dimensionType === 'COMPLEX<json>' ? 'json' : dimensionType,
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name: h,
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};
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});
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|
|
|
@ -16,15 +16,15 @@
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* limitations under the License.
|
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*/
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import { CSV_SAMPLE } from '../../utils/sampler.mock';
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import { CSV_SAMPLE, JSON_SAMPLE } from '../../utils/sampler.mock';
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import type { IngestionSpec } from './ingestion-spec';
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import {
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adjustId,
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cleanSpec,
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guessColumnTypeFromHeaderAndRows,
|
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guessColumnTypeFromInput,
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guessInputFormat,
|
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guessColumnTypeFromSampleResponse,
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guessSimpleInputFormat,
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updateSchemaWithSample,
|
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upgradeSpec,
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} from './ingestion-spec';
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|
@ -565,26 +565,26 @@ describe('ingestion-spec', () => {
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});
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});
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describe('guessInputFormat', () => {
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describe('guessSimpleInputFormat', () => {
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it('works for parquet', () => {
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expect(guessInputFormat(['PAR1lol']).type).toEqual('parquet');
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expect(guessSimpleInputFormat(['PAR1lol']).type).toEqual('parquet');
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});
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it('works for orc', () => {
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expect(guessInputFormat(['ORClol']).type).toEqual('orc');
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expect(guessSimpleInputFormat(['ORClol']).type).toEqual('orc');
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});
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it('works for AVRO', () => {
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expect(guessInputFormat(['Obj\x01lol']).type).toEqual('avro_ocf');
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expect(guessInputFormat(['Obj1lol']).type).toEqual('regex');
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expect(guessSimpleInputFormat(['Obj\x01lol']).type).toEqual('avro_ocf');
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expect(guessSimpleInputFormat(['Obj1lol']).type).toEqual('regex');
|
||||
});
|
||||
|
||||
it('works for JSON (strict)', () => {
|
||||
expect(guessInputFormat(['{"a":1}'])).toEqual({ type: 'json' });
|
||||
expect(guessSimpleInputFormat(['{"a":1}'])).toEqual({ type: 'json' });
|
||||
});
|
||||
|
||||
it('works for JSON (lax)', () => {
|
||||
expect(guessInputFormat([`{hello:'world'}`])).toEqual({
|
||||
expect(guessSimpleInputFormat([`{hello:'world'}`])).toEqual({
|
||||
type: 'json',
|
||||
featureSpec: {
|
||||
ALLOW_BACKSLASH_ESCAPING_ANY_CHARACTER: true,
|
||||
|
@ -602,14 +602,14 @@ describe('ingestion-spec', () => {
|
|||
});
|
||||
|
||||
it('works for CSV (with header)', () => {
|
||||
expect(guessInputFormat(['A,B,"X,1",Y'])).toEqual({
|
||||
expect(guessSimpleInputFormat(['A,B,"X,1",Y'])).toEqual({
|
||||
type: 'csv',
|
||||
findColumnsFromHeader: true,
|
||||
});
|
||||
});
|
||||
|
||||
it('works for CSV (no header)', () => {
|
||||
expect(guessInputFormat(['"A,1","B,2",1,2'])).toEqual({
|
||||
expect(guessSimpleInputFormat(['"A,1","B,2",1,2'])).toEqual({
|
||||
type: 'csv',
|
||||
findColumnsFromHeader: false,
|
||||
columns: ['column1', 'column2', 'column3', 'column4'],
|
||||
|
@ -617,14 +617,14 @@ describe('ingestion-spec', () => {
|
|||
});
|
||||
|
||||
it('works for TSV (with header)', () => {
|
||||
expect(guessInputFormat(['A\tB\tX\tY'])).toEqual({
|
||||
expect(guessSimpleInputFormat(['A\tB\tX\tY'])).toEqual({
|
||||
type: 'tsv',
|
||||
findColumnsFromHeader: true,
|
||||
});
|
||||
});
|
||||
|
||||
it('works for TSV (no header)', () => {
|
||||
expect(guessInputFormat(['A\tB\t1\t2\t3\t4\t5\t6\t7\t8\t9'])).toEqual({
|
||||
expect(guessSimpleInputFormat(['A\tB\t1\t2\t3\t4\t5\t6\t7\t8\t9'])).toEqual({
|
||||
type: 'tsv',
|
||||
findColumnsFromHeader: false,
|
||||
columns: [
|
||||
|
@ -644,7 +644,7 @@ describe('ingestion-spec', () => {
|
|||
});
|
||||
|
||||
it('works for TSV with ;', () => {
|
||||
const inputFormat = guessInputFormat(['A;B;X;Y']);
|
||||
const inputFormat = guessSimpleInputFormat(['A;B;X;Y']);
|
||||
expect(inputFormat).toEqual({
|
||||
type: 'tsv',
|
||||
delimiter: ';',
|
||||
|
@ -653,7 +653,7 @@ describe('ingestion-spec', () => {
|
|||
});
|
||||
|
||||
it('works for TSV with |', () => {
|
||||
const inputFormat = guessInputFormat(['A|B|X|Y']);
|
||||
const inputFormat = guessSimpleInputFormat(['A|B|X|Y']);
|
||||
expect(inputFormat).toEqual({
|
||||
type: 'tsv',
|
||||
delimiter: '|',
|
||||
|
@ -662,7 +662,7 @@ describe('ingestion-spec', () => {
|
|||
});
|
||||
|
||||
it('works for regex', () => {
|
||||
expect(guessInputFormat(['A/B/X/Y'])).toEqual({
|
||||
expect(guessSimpleInputFormat(['A/B/X/Y'])).toEqual({
|
||||
type: 'regex',
|
||||
pattern: '([\\s\\S]*)',
|
||||
columns: ['line'],
|
||||
|
@ -745,30 +745,19 @@ describe('spec utils', () => {
|
|||
});
|
||||
});
|
||||
|
||||
describe('guessColumnTypeFromHeaderAndRows', () => {
|
||||
it('works in empty dataset', () => {
|
||||
expect(guessColumnTypeFromHeaderAndRows({ header: ['c0'], rows: [] }, 'c0', false)).toEqual(
|
||||
'string',
|
||||
);
|
||||
});
|
||||
|
||||
describe('guessColumnTypeFromSampleResponse', () => {
|
||||
it('works for generic dataset', () => {
|
||||
expect(guessColumnTypeFromHeaderAndRows(CSV_SAMPLE, 'user', false)).toEqual('string');
|
||||
expect(guessColumnTypeFromHeaderAndRows(CSV_SAMPLE, 'followers', false)).toEqual('string');
|
||||
expect(guessColumnTypeFromHeaderAndRows(CSV_SAMPLE, 'followers', true)).toEqual('long');
|
||||
expect(guessColumnTypeFromHeaderAndRows(CSV_SAMPLE, 'spend', true)).toEqual('double');
|
||||
expect(guessColumnTypeFromHeaderAndRows(CSV_SAMPLE, 'nums', false)).toEqual('string');
|
||||
expect(guessColumnTypeFromHeaderAndRows(CSV_SAMPLE, 'nums', true)).toEqual('string');
|
||||
expect(guessColumnTypeFromSampleResponse(CSV_SAMPLE, 'user', false)).toEqual('string');
|
||||
expect(guessColumnTypeFromSampleResponse(CSV_SAMPLE, 'followers', false)).toEqual('string');
|
||||
expect(guessColumnTypeFromSampleResponse(CSV_SAMPLE, 'followers', true)).toEqual('long');
|
||||
expect(guessColumnTypeFromSampleResponse(CSV_SAMPLE, 'spend', true)).toEqual('double');
|
||||
expect(guessColumnTypeFromSampleResponse(CSV_SAMPLE, 'nums', false)).toEqual('string');
|
||||
expect(guessColumnTypeFromSampleResponse(CSV_SAMPLE, 'nums', true)).toEqual('string');
|
||||
});
|
||||
});
|
||||
|
||||
it('updateSchemaWithSample', () => {
|
||||
const withRollup = updateSchemaWithSample(
|
||||
ingestionSpec,
|
||||
{ header: ['header'], rows: [] },
|
||||
'specific',
|
||||
true,
|
||||
);
|
||||
const withRollup = updateSchemaWithSample(ingestionSpec, JSON_SAMPLE, 'specific', true);
|
||||
|
||||
expect(withRollup).toMatchInlineSnapshot(`
|
||||
Object {
|
||||
|
@ -777,7 +766,10 @@ describe('spec utils', () => {
|
|||
"dataSource": "wikipedia",
|
||||
"dimensionsSpec": Object {
|
||||
"dimensions": Array [
|
||||
"header",
|
||||
"user",
|
||||
"id",
|
||||
"tags",
|
||||
"nums",
|
||||
],
|
||||
},
|
||||
"granularitySpec": Object {
|
||||
|
@ -790,6 +782,16 @@ describe('spec utils', () => {
|
|||
"name": "count",
|
||||
"type": "count",
|
||||
},
|
||||
Object {
|
||||
"fieldName": "followers",
|
||||
"name": "sum_followers",
|
||||
"type": "longSum",
|
||||
},
|
||||
Object {
|
||||
"fieldName": "spend",
|
||||
"name": "sum_spend",
|
||||
"type": "doubleSum",
|
||||
},
|
||||
],
|
||||
"timestampSpec": Object {
|
||||
"column": "timestamp",
|
||||
|
@ -820,12 +822,7 @@ describe('spec utils', () => {
|
|||
}
|
||||
`);
|
||||
|
||||
const noRollup = updateSchemaWithSample(
|
||||
ingestionSpec,
|
||||
{ header: ['header'], rows: [] },
|
||||
'specific',
|
||||
false,
|
||||
);
|
||||
const noRollup = updateSchemaWithSample(ingestionSpec, JSON_SAMPLE, 'specific', false);
|
||||
|
||||
expect(noRollup).toMatchInlineSnapshot(`
|
||||
Object {
|
||||
|
@ -834,7 +831,18 @@ describe('spec utils', () => {
|
|||
"dataSource": "wikipedia",
|
||||
"dimensionsSpec": Object {
|
||||
"dimensions": Array [
|
||||
"header",
|
||||
"user",
|
||||
Object {
|
||||
"name": "followers",
|
||||
"type": "long",
|
||||
},
|
||||
Object {
|
||||
"name": "spend",
|
||||
"type": "double",
|
||||
},
|
||||
"id",
|
||||
"tags",
|
||||
"nums",
|
||||
],
|
||||
},
|
||||
"granularitySpec": Object {
|
||||
|
|
|
@ -34,12 +34,13 @@ import {
|
|||
EMPTY_ARRAY,
|
||||
EMPTY_OBJECT,
|
||||
filterMap,
|
||||
findMap,
|
||||
isSimpleArray,
|
||||
oneOf,
|
||||
parseCsvLine,
|
||||
typeIs,
|
||||
} from '../../utils';
|
||||
import type { SampleHeaderAndRows } from '../../utils/sampler';
|
||||
import type { SampleResponse } from '../../utils/sampler';
|
||||
import type { DimensionsSpec } from '../dimension-spec/dimension-spec';
|
||||
import {
|
||||
getDimensionSpecName,
|
||||
|
@ -269,6 +270,9 @@ export interface DataSchema {
|
|||
export type DimensionMode = 'specific' | 'auto-detect';
|
||||
|
||||
export function getDimensionMode(spec: Partial<IngestionSpec>): DimensionMode {
|
||||
if (deepGet(spec, 'spec.dataSchema.dimensionsSpec.useSchemaDiscovery') === true) {
|
||||
return 'auto-detect';
|
||||
}
|
||||
const dimensions = deepGet(spec, 'spec.dataSchema.dimensionsSpec.dimensions') || EMPTY_ARRAY;
|
||||
return Array.isArray(dimensions) && dimensions.length === 0 ? 'auto-detect' : 'specific';
|
||||
}
|
||||
|
@ -893,6 +897,7 @@ export function getIoConfigFormFields(ingestionComboType: IngestionComboType): F
|
|||
label: 'Bootstrap servers',
|
||||
type: 'string',
|
||||
required: true,
|
||||
placeholder: 'kafka_broker_host:9092',
|
||||
info: (
|
||||
<>
|
||||
<ExternalLink
|
||||
|
@ -914,6 +919,7 @@ export function getIoConfigFormFields(ingestionComboType: IngestionComboType): F
|
|||
type: 'string',
|
||||
required: true,
|
||||
defined: typeIs('kafka'),
|
||||
placeholder: 'topic_name',
|
||||
},
|
||||
{
|
||||
name: 'consumerProperties',
|
||||
|
@ -2134,13 +2140,13 @@ export function updateIngestionType(
|
|||
}
|
||||
|
||||
export function issueWithSampleData(
|
||||
sampleData: string[],
|
||||
sampleData: SampleResponse,
|
||||
spec: Partial<IngestionSpec>,
|
||||
): JSX.Element | undefined {
|
||||
if (isStreamingSpec(spec)) return;
|
||||
|
||||
if (sampleData.length) {
|
||||
const firstData = sampleData[0];
|
||||
const firstData: string = findMap(sampleData.data, l => l.input?.raw);
|
||||
if (firstData) return;
|
||||
|
||||
if (firstData === '{') {
|
||||
return (
|
||||
|
@ -2161,20 +2167,25 @@ export function issueWithSampleData(
|
|||
</>
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
return;
|
||||
}
|
||||
|
||||
export function fillInputFormatIfNeeded(
|
||||
spec: Partial<IngestionSpec>,
|
||||
sampleData: string[],
|
||||
sampleResponse: SampleResponse,
|
||||
): Partial<IngestionSpec> {
|
||||
if (deepGet(spec, 'spec.ioConfig.inputFormat.type')) return spec;
|
||||
|
||||
return deepSet(
|
||||
spec,
|
||||
'spec.ioConfig.inputFormat',
|
||||
guessInputFormat(sampleData, isStreamingSpec(spec)),
|
||||
getSpecType(spec) === 'kafka'
|
||||
? guessKafkaInputFormat(filterMap(sampleResponse.data, l => l.input))
|
||||
: guessSimpleInputFormat(
|
||||
filterMap(sampleResponse.data, l => l.input?.raw),
|
||||
isStreamingSpec(spec),
|
||||
),
|
||||
);
|
||||
}
|
||||
|
||||
|
@ -2182,8 +2193,23 @@ function noNumbers(xs: string[]): boolean {
|
|||
return xs.every(x => isNaN(Number(x)));
|
||||
}
|
||||
|
||||
export function guessInputFormat(sampleData: string[], canBeMultiLineJson = false): InputFormat {
|
||||
let sampleDatum = sampleData[0];
|
||||
export function guessKafkaInputFormat(sampleRaw: Record<string, any>[]): InputFormat {
|
||||
const hasHeader = sampleRaw.some(x => Object.keys(x).some(k => k.startsWith('kafka.header.')));
|
||||
const keys = filterMap(sampleRaw, x => x['kafka.key']);
|
||||
const payloads = filterMap(sampleRaw, x => x.raw);
|
||||
return {
|
||||
type: 'kafka',
|
||||
headerFormat: hasHeader ? { type: 'string' } : undefined,
|
||||
keyFormat: keys.length ? guessSimpleInputFormat(keys, true) : undefined,
|
||||
valueFormat: guessSimpleInputFormat(payloads, true),
|
||||
};
|
||||
}
|
||||
|
||||
export function guessSimpleInputFormat(
|
||||
sampleRaw: string[],
|
||||
canBeMultiLineJson = false,
|
||||
): InputFormat {
|
||||
let sampleDatum = sampleRaw[0];
|
||||
if (sampleDatum) {
|
||||
sampleDatum = String(sampleDatum); // Really ensure it is a string
|
||||
|
||||
|
@ -2319,11 +2345,11 @@ function inputFormatFromType(options: InputFormatFromTypeOptions): InputFormat {
|
|||
|
||||
// ------------------------
|
||||
|
||||
export function guessIsArrayFromHeaderAndRows(
|
||||
headerAndRows: SampleHeaderAndRows,
|
||||
export function guessIsArrayFromSampleResponse(
|
||||
sampleResponse: SampleResponse,
|
||||
column: string,
|
||||
): boolean {
|
||||
return headerAndRows.rows.some(r => isSimpleArray(r.input?.[column]));
|
||||
return sampleResponse.data.some(r => isSimpleArray(r.input?.[column]));
|
||||
}
|
||||
|
||||
export function guessColumnTypeFromInput(
|
||||
|
@ -2355,13 +2381,13 @@ export function guessColumnTypeFromInput(
|
|||
}
|
||||
}
|
||||
|
||||
export function guessColumnTypeFromHeaderAndRows(
|
||||
headerAndRows: SampleHeaderAndRows,
|
||||
export function guessColumnTypeFromSampleResponse(
|
||||
sampleResponse: SampleResponse,
|
||||
column: string,
|
||||
guessNumericStringsAsNumbers: boolean,
|
||||
): string {
|
||||
return guessColumnTypeFromInput(
|
||||
filterMap(headerAndRows.rows, r => r.input?.[column]),
|
||||
filterMap(sampleResponse.data, r => r.input?.[column]),
|
||||
guessNumericStringsAsNumbers,
|
||||
);
|
||||
}
|
||||
|
@ -2391,7 +2417,7 @@ function getTypeHintsFromSpec(spec: Partial<IngestionSpec>): Record<string, stri
|
|||
|
||||
export function updateSchemaWithSample(
|
||||
spec: Partial<IngestionSpec>,
|
||||
headerAndRows: SampleHeaderAndRows,
|
||||
sampleResponse: SampleResponse,
|
||||
dimensionMode: DimensionMode,
|
||||
rollup: boolean,
|
||||
forcePartitionInitialization = false,
|
||||
|
@ -2404,26 +2430,25 @@ export function updateSchemaWithSample(
|
|||
let newSpec = spec;
|
||||
|
||||
if (dimensionMode === 'auto-detect') {
|
||||
newSpec = deepDelete(newSpec, 'spec.dataSchema.dimensionsSpec.dimensions');
|
||||
newSpec = deepSet(newSpec, 'spec.dataSchema.dimensionsSpec.useSchemaDiscovery', true);
|
||||
newSpec = deepSet(newSpec, 'spec.dataSchema.dimensionsSpec.includeAllDimensions', true);
|
||||
newSpec = deepSet(newSpec, 'spec.dataSchema.dimensionsSpec.dimensionExclusions', []);
|
||||
newSpec = deepDelete(newSpec, 'spec.dataSchema.dimensionsSpec.dimensions');
|
||||
} else {
|
||||
newSpec = deepDelete(newSpec, 'spec.dataSchema.dimensionsSpec.useSchemaDiscovery');
|
||||
newSpec = deepDelete(newSpec, 'spec.dataSchema.dimensionsSpec.includeAllDimensions');
|
||||
newSpec = deepDelete(newSpec, 'spec.dataSchema.dimensionsSpec.dimensionExclusions');
|
||||
|
||||
const dimensions = getDimensionSpecs(
|
||||
headerAndRows,
|
||||
typeHints,
|
||||
guessNumericStringsAsNumbers,
|
||||
rollup,
|
||||
newSpec = deepSet(
|
||||
newSpec,
|
||||
'spec.dataSchema.dimensionsSpec.dimensions',
|
||||
getDimensionSpecs(sampleResponse, typeHints, guessNumericStringsAsNumbers, rollup),
|
||||
);
|
||||
if (dimensions) {
|
||||
newSpec = deepSet(newSpec, 'spec.dataSchema.dimensionsSpec.dimensions', dimensions);
|
||||
}
|
||||
}
|
||||
|
||||
if (rollup) {
|
||||
newSpec = deepSet(newSpec, 'spec.dataSchema.granularitySpec.queryGranularity', 'hour');
|
||||
|
||||
const metrics = getMetricSpecs(headerAndRows, typeHints, guessNumericStringsAsNumbers);
|
||||
const metrics = getMetricSpecs(sampleResponse, typeHints, guessNumericStringsAsNumbers);
|
||||
if (metrics) {
|
||||
newSpec = deepSet(newSpec, 'spec.dataSchema.metricsSpec', metrics);
|
||||
}
|
||||
|
|
|
@ -22,7 +22,7 @@ import React from 'react';
|
|||
import type { Field } from '../../components';
|
||||
import { AutoForm, ExternalLink } from '../../components';
|
||||
import { getLink } from '../../links';
|
||||
import { compact, oneOf, typeIs } from '../../utils';
|
||||
import { compact, deepGet, deepSet, oneOf, typeIs } from '../../utils';
|
||||
import type { FlattenSpec } from '../flatten-spec/flatten-spec';
|
||||
|
||||
export interface InputFormat {
|
||||
|
@ -39,6 +39,14 @@ export interface InputFormat {
|
|||
readonly keepNullColumns?: boolean;
|
||||
readonly assumeNewlineDelimited?: boolean;
|
||||
readonly useJsonNodeReader?: boolean;
|
||||
|
||||
// type: kafka
|
||||
readonly timestampColumnName?: string;
|
||||
readonly headerFormat?: { type: 'string'; encoding?: string };
|
||||
readonly headerColumnPrefix?: string;
|
||||
readonly keyFormat?: InputFormat;
|
||||
readonly keyColumnName?: string;
|
||||
readonly valueFormat?: InputFormat;
|
||||
}
|
||||
|
||||
function generateInputFormatFields(streaming: boolean) {
|
||||
|
@ -88,7 +96,7 @@ function generateInputFormatFields(streaming: boolean) {
|
|||
name: 'assumeNewlineDelimited',
|
||||
type: 'boolean',
|
||||
defined: typeIs('json'),
|
||||
disabled: (inputFormat: InputFormat) => inputFormat.useJsonNodeReader,
|
||||
disabled: inputFormat => Boolean(inputFormat.useJsonNodeReader),
|
||||
defaultValue: false,
|
||||
info: (
|
||||
<>
|
||||
|
@ -115,10 +123,10 @@ function generateInputFormatFields(streaming: boolean) {
|
|||
streaming
|
||||
? {
|
||||
name: 'useJsonNodeReader',
|
||||
title: 'Use JSON node reader',
|
||||
label: 'Use JSON node reader',
|
||||
type: 'boolean',
|
||||
defined: typeIs('json'),
|
||||
disabled: (inputFormat: InputFormat) => inputFormat.assumeNewlineDelimited,
|
||||
disabled: inputFormat => Boolean(inputFormat.assumeNewlineDelimited),
|
||||
defaultValue: false,
|
||||
info: (
|
||||
<>
|
||||
|
@ -224,11 +232,274 @@ function generateInputFormatFields(streaming: boolean) {
|
|||
] as (Field<InputFormat> | undefined)[]);
|
||||
}
|
||||
|
||||
export const INPUT_FORMAT_FIELDS: Field<InputFormat>[] = generateInputFormatFields(false);
|
||||
export const BATCH_INPUT_FORMAT_FIELDS: Field<InputFormat>[] = generateInputFormatFields(false);
|
||||
export const STREAMING_INPUT_FORMAT_FIELDS: Field<InputFormat>[] = generateInputFormatFields(true);
|
||||
export const KAFKA_METADATA_INPUT_FORMAT_FIELDS: Field<InputFormat>[] = [
|
||||
{
|
||||
name: 'timestampColumnName',
|
||||
label: 'Kafka timestamp column name',
|
||||
type: 'string',
|
||||
defaultValue: 'kafka.timestamp',
|
||||
defined: typeIs('kafka'),
|
||||
info: `Name of the column for the kafka record's timestamp.`,
|
||||
},
|
||||
|
||||
// -----------------------------------------------------
|
||||
// keyFormat fields
|
||||
|
||||
{
|
||||
name: 'keyFormat.type',
|
||||
label: 'Kafka key input format',
|
||||
type: 'string',
|
||||
suggestions: [
|
||||
undefined,
|
||||
'json',
|
||||
'csv',
|
||||
'tsv',
|
||||
'parquet',
|
||||
'orc',
|
||||
'avro_ocf',
|
||||
'avro_stream',
|
||||
'regex',
|
||||
],
|
||||
placeholder: `(don't parse Kafka key)`,
|
||||
defined: typeIs('kafka'),
|
||||
info: (
|
||||
<>
|
||||
<p>The parser used to parse the key of the Kafka message.</p>
|
||||
<p>
|
||||
For more information see{' '}
|
||||
<ExternalLink href={`${getLink('DOCS')}/ingestion/data-formats.html`}>
|
||||
the documentation
|
||||
</ExternalLink>
|
||||
.
|
||||
</p>
|
||||
</>
|
||||
),
|
||||
adjustment: inputFormat => {
|
||||
const keyFormatType = deepGet(inputFormat, 'keyFormat.type');
|
||||
// If the user selects one of these formats then populate the columns (that are in any case meaningless in this context)
|
||||
// with an initial value.
|
||||
switch (keyFormatType) {
|
||||
case 'regex':
|
||||
inputFormat = deepSet(inputFormat, 'keyFormat.pattern', '([\\s\\S]*)');
|
||||
inputFormat = deepSet(inputFormat, 'keyFormat.columns', ['x']);
|
||||
break;
|
||||
|
||||
case 'csv':
|
||||
case 'tsv':
|
||||
inputFormat = deepSet(inputFormat, 'keyFormat.findColumnsFromHeader', false);
|
||||
inputFormat = deepSet(inputFormat, 'keyFormat.columns', ['x']);
|
||||
break;
|
||||
}
|
||||
return inputFormat;
|
||||
},
|
||||
},
|
||||
{
|
||||
name: 'keyFormat.featureSpec',
|
||||
label: 'Kafka key JSON parser features',
|
||||
type: 'json',
|
||||
defined: inputFormat => deepGet(inputFormat, 'keyFormat.type') === 'json',
|
||||
hideInMore: true,
|
||||
info: (
|
||||
<>
|
||||
<p>
|
||||
<ExternalLink href="https://github.com/FasterXML/jackson-core/wiki/JsonParser-Features">
|
||||
JSON parser features
|
||||
</ExternalLink>{' '}
|
||||
supported by Jackson library. Those features will be applied when parsing the input JSON
|
||||
data.
|
||||
</p>
|
||||
<p>
|
||||
Example:{' '}
|
||||
<Code>{`{ "ALLOW_SINGLE_QUOTES": true, "ALLOW_UNQUOTED_FIELD_NAMES": true }`}</Code>
|
||||
</p>
|
||||
</>
|
||||
),
|
||||
},
|
||||
{
|
||||
name: 'keyFormat.assumeNewlineDelimited',
|
||||
label: 'Kafka key assume newline delimited',
|
||||
type: 'boolean',
|
||||
defined: inputFormat => deepGet(inputFormat, 'keyFormat.type') === 'json',
|
||||
disabled: inputFormat => Boolean(inputFormat.useJsonNodeReader),
|
||||
defaultValue: false,
|
||||
hideInMore: true,
|
||||
info: (
|
||||
<>
|
||||
<p>
|
||||
In streaming ingestion, multi-line JSON events can be ingested (i.e. where a single JSON
|
||||
event spans multiple lines). However, if a parsing exception occurs, all JSON events that
|
||||
are present in the same streaming record will be discarded.
|
||||
</p>
|
||||
<p>
|
||||
<Code>assumeNewlineDelimited</Code> and <Code>useJsonNodeReader</Code> (at most one can be{' '}
|
||||
<Code>true</Code>) affect only how parsing exceptions are handled.
|
||||
</p>
|
||||
<p>
|
||||
If the input is known to be newline delimited JSON (each individual JSON event is
|
||||
contained in a single line, separated by newlines), setting this option to true allows for
|
||||
more flexible parsing exception handling. Only the lines with invalid JSON syntax will be
|
||||
discarded, while lines containing valid JSON events will still be ingested.
|
||||
</p>
|
||||
</>
|
||||
),
|
||||
},
|
||||
{
|
||||
name: 'keyFormat.useJsonNodeReader',
|
||||
label: 'Kafka key use JSON node reader',
|
||||
type: 'boolean',
|
||||
defined: inputFormat => deepGet(inputFormat, 'keyFormat.type') === 'json',
|
||||
disabled: inputFormat => Boolean(inputFormat.assumeNewlineDelimited),
|
||||
defaultValue: false,
|
||||
hideInMore: true,
|
||||
info: (
|
||||
<>
|
||||
{' '}
|
||||
<p>
|
||||
In streaming ingestion, multi-line JSON events can be ingested (i.e. where a single JSON
|
||||
event spans multiple lines). However, if a parsing exception occurs, all JSON events that
|
||||
are present in the same streaming record will be discarded.
|
||||
</p>
|
||||
<p>
|
||||
<Code>assumeNewlineDelimited</Code> and <Code>useJsonNodeReader</Code> (at most one can be{' '}
|
||||
<Code>true</Code>) affect only how parsing exceptions are handled.
|
||||
</p>
|
||||
<p>
|
||||
When ingesting multi-line JSON events, enabling this option will enable the use of a JSON
|
||||
parser which will retain any valid JSON events encountered within a streaming record prior
|
||||
to when a parsing exception occurred.
|
||||
</p>
|
||||
</>
|
||||
),
|
||||
},
|
||||
{
|
||||
name: 'keyFormat.delimiter',
|
||||
label: 'Kafka key delimiter',
|
||||
type: 'string',
|
||||
defaultValue: '\t',
|
||||
suggestions: ['\t', ';', '|', '#'],
|
||||
defined: inputFormat => deepGet(inputFormat, 'keyFormat.type') === 'tsv',
|
||||
info: <>A custom delimiter for data values.</>,
|
||||
},
|
||||
{
|
||||
name: 'keyFormat.pattern',
|
||||
label: 'Kafka key pattern',
|
||||
type: 'string',
|
||||
defined: inputFormat => deepGet(inputFormat, 'keyFormat.type') === 'regex',
|
||||
required: true,
|
||||
},
|
||||
{
|
||||
name: 'keyFormat.skipHeaderRows',
|
||||
label: 'Kafka key skip header rows',
|
||||
type: 'number',
|
||||
defaultValue: 0,
|
||||
defined: inputFormat => oneOf(deepGet(inputFormat, 'keyFormat.type'), 'csv', 'tsv'),
|
||||
min: 0,
|
||||
info: (
|
||||
<>
|
||||
If this is set, skip the first <Code>skipHeaderRows</Code> rows from each file.
|
||||
</>
|
||||
),
|
||||
},
|
||||
{
|
||||
name: 'keyFormat.findColumnsFromHeader',
|
||||
label: 'Kafka key find columns from header',
|
||||
type: 'boolean',
|
||||
defined: inputFormat => oneOf(deepGet(inputFormat, 'keyFormat.type'), 'csv', 'tsv'),
|
||||
required: true,
|
||||
hideInMore: true,
|
||||
info: (
|
||||
<>
|
||||
If this is set, find the column names from the header row. Note that
|
||||
<Code>skipHeaderRows</Code> will be applied before finding column names from the header. For
|
||||
example, if you set <Code>skipHeaderRows</Code> to 2 and <Code>findColumnsFromHeader</Code>{' '}
|
||||
to true, the task will skip the first two lines and then extract column information from the
|
||||
third line.
|
||||
</>
|
||||
),
|
||||
},
|
||||
{
|
||||
name: 'keyFormat.columns',
|
||||
label: 'Kafka key columns',
|
||||
type: 'string-array',
|
||||
required: true,
|
||||
defined: inputFormat =>
|
||||
(oneOf(deepGet(inputFormat, 'keyFormat.type'), 'csv', 'tsv') &&
|
||||
deepGet(inputFormat, 'keyFormat.findColumnsFromHeader') === false) ||
|
||||
deepGet(inputFormat, 'keyFormat.type') === 'regex',
|
||||
hideInMore: true,
|
||||
info: (
|
||||
<>
|
||||
Only the value of the first column will be read, the name of the column will be ignored so
|
||||
enter anything here.
|
||||
</>
|
||||
),
|
||||
},
|
||||
{
|
||||
name: 'keyFormat.listDelimiter',
|
||||
label: 'Kafka key list delimiter',
|
||||
type: 'string',
|
||||
defaultValue: '\x01',
|
||||
suggestions: ['\x01', '\x00'],
|
||||
defined: inputFormat => oneOf(deepGet(inputFormat, 'keyFormat.type'), 'csv', 'tsv', 'regex'),
|
||||
info: <>A custom delimiter for multi-value dimensions.</>,
|
||||
},
|
||||
{
|
||||
name: 'keyFormat.binaryAsString',
|
||||
label: 'Kafka key list binary as string',
|
||||
type: 'boolean',
|
||||
defaultValue: false,
|
||||
defined: inputFormat =>
|
||||
oneOf(deepGet(inputFormat, 'valueFormat.type'), 'parquet', 'orc', 'avro_ocf', 'avro_stream'),
|
||||
info: (
|
||||
<>
|
||||
Specifies if the binary column which is not logically marked as a string should be treated
|
||||
as a UTF-8 encoded string.
|
||||
</>
|
||||
),
|
||||
},
|
||||
|
||||
// keyColumnName
|
||||
{
|
||||
name: 'keyColumnName',
|
||||
label: 'Kafka key column name',
|
||||
type: 'string',
|
||||
defaultValue: 'kafka.key',
|
||||
defined: inputFormat => Boolean(deepGet(inputFormat, 'keyFormat.type')),
|
||||
info: `Custom prefix for all the header columns.`,
|
||||
},
|
||||
|
||||
// -----------------------------------------------------
|
||||
|
||||
{
|
||||
name: 'headerFormat.type',
|
||||
label: 'Kafka header format type',
|
||||
type: 'string',
|
||||
defined: typeIs('kafka'),
|
||||
placeholder: `(don't parse Kafka herders)`,
|
||||
suggestions: [undefined, 'string'],
|
||||
},
|
||||
{
|
||||
name: 'headerFormat.encoding',
|
||||
label: 'Kafka header format encoding',
|
||||
type: 'string',
|
||||
defaultValue: 'UTF-8',
|
||||
defined: inputFormat => deepGet(inputFormat, 'headerFormat.type') === 'string',
|
||||
suggestions: ['UTF-8', 'UTF-16BE', 'UTF-16LE', 'UTF-16', 'US-ASCII', 'ISO-8859-1'],
|
||||
},
|
||||
{
|
||||
name: 'headerColumnPrefix',
|
||||
label: 'Kafka header column prefix',
|
||||
type: 'string',
|
||||
defaultValue: 'kafka.header.',
|
||||
defined: inputFormat => deepGet(inputFormat, 'headerFormat.type') === 'string',
|
||||
info: `Custom prefix for all the header columns.`,
|
||||
},
|
||||
];
|
||||
|
||||
export function issueWithInputFormat(inputFormat: InputFormat | undefined): string | undefined {
|
||||
return AutoForm.issueWithModel(inputFormat, INPUT_FORMAT_FIELDS);
|
||||
return AutoForm.issueWithModel(inputFormat, BATCH_INPUT_FORMAT_FIELDS);
|
||||
}
|
||||
|
||||
export const inputFormatCanProduceNestedData: (inputFormat: InputFormat) => boolean = typeIs(
|
||||
|
|
|
@ -16,16 +16,14 @@
|
|||
* limitations under the License.
|
||||
*/
|
||||
|
||||
import { JSON_SAMPLE } from '../../utils/sampler.mock';
|
||||
import { EMPTY_SAMPLE, JSON_SAMPLE } from '../../utils/sampler.mock';
|
||||
|
||||
import { getMetricSpecs } from './metric-spec';
|
||||
|
||||
describe('metric-spec', () => {
|
||||
describe('getMetricSecs', () => {
|
||||
it('works for empty', () => {
|
||||
expect(getMetricSpecs({ header: ['header'], rows: [] }, {}, false)).toEqual([
|
||||
{ name: 'count', type: 'count' },
|
||||
]);
|
||||
expect(getMetricSpecs(EMPTY_SAMPLE, {}, false)).toEqual([{ name: 'count', type: 'count' }]);
|
||||
});
|
||||
|
||||
it('works with json', () => {
|
||||
|
|
|
@ -23,8 +23,8 @@ import type { Field } from '../../components';
|
|||
import { ExternalLink } from '../../components';
|
||||
import { getLink } from '../../links';
|
||||
import { filterMap, typeIs } from '../../utils';
|
||||
import type { SampleHeaderAndRows } from '../../utils/sampler';
|
||||
import { guessColumnTypeFromHeaderAndRows } from '../ingestion-spec/ingestion-spec';
|
||||
import type { SampleResponse } from '../../utils/sampler';
|
||||
import { guessColumnTypeFromSampleResponse } from '../ingestion-spec/ingestion-spec';
|
||||
|
||||
export interface MetricSpec {
|
||||
readonly type: string;
|
||||
|
@ -388,16 +388,17 @@ export function getMetricSpecOutputType(metricSpec: MetricSpec): string | undefi
|
|||
}
|
||||
|
||||
export function getMetricSpecs(
|
||||
headerAndRows: SampleHeaderAndRows,
|
||||
sampleResponse: SampleResponse,
|
||||
typeHints: Record<string, string>,
|
||||
guessNumericStringsAsNumbers: boolean,
|
||||
): MetricSpec[] {
|
||||
return [{ name: 'count', type: 'count' }].concat(
|
||||
filterMap(headerAndRows.header, h => {
|
||||
filterMap(sampleResponse.logicalSegmentSchema, s => {
|
||||
const h = s.name;
|
||||
if (h === '__time') return;
|
||||
const type =
|
||||
typeHints[h] ||
|
||||
guessColumnTypeFromHeaderAndRows(headerAndRows, h, guessNumericStringsAsNumbers);
|
||||
guessColumnTypeFromSampleResponse(sampleResponse, h, guessNumericStringsAsNumbers);
|
||||
switch (type) {
|
||||
case 'double':
|
||||
return { name: `sum_${h}`, type: 'doubleSum', fieldName: h };
|
||||
|
|
|
@ -16,8 +16,9 @@
|
|||
* limitations under the License.
|
||||
*/
|
||||
|
||||
import { timeFormatMatches } from './time';
|
||||
import { possibleDruidFormatForValues, timeFormatMatches } from './time';
|
||||
|
||||
describe('time', () => {
|
||||
describe('timeFormatMatches', () => {
|
||||
it('works for auto', () => {
|
||||
expect(timeFormatMatches('auto', '2019-05-22 22:42:51+0000')).toBeTruthy();
|
||||
|
@ -28,3 +29,18 @@ describe('timeFormatMatches', () => {
|
|||
expect(timeFormatMatches('iso', '2019-05-22 22:42:51+0000')).toBeFalsy();
|
||||
});
|
||||
});
|
||||
|
||||
describe('possibleDruidFormatForValues', () => {
|
||||
it('works in empty case', () => {
|
||||
expect(possibleDruidFormatForValues([])).toBeUndefined();
|
||||
});
|
||||
|
||||
it('does not react to small numbers', () => {
|
||||
expect(possibleDruidFormatForValues([12, 234, 3432])).toBeUndefined();
|
||||
});
|
||||
|
||||
it('works for auto', () => {
|
||||
expect(possibleDruidFormatForValues(['2019-05-22 22:42:51'])).toEqual('auto');
|
||||
});
|
||||
});
|
||||
});
|
||||
|
|
|
@ -86,6 +86,7 @@ export function timeFormatMatches(format: string, value: string | number | bigin
|
|||
}
|
||||
|
||||
export function possibleDruidFormatForValues(values: any[]): string | undefined {
|
||||
if (!values.length) return;
|
||||
return ALL_FORMAT_VALUES.find(format => {
|
||||
return values.every(value => timeFormatMatches(format, value));
|
||||
});
|
||||
|
|
|
@ -54,9 +54,6 @@ interface ConsoleConfig {
|
|||
// A set of custom headers name/value to set on every AJAX request
|
||||
customHeaders?: Record<string, string>;
|
||||
|
||||
// The URL for where to load the example manifest, a JSON document that tells the console where to find all the example datasets
|
||||
exampleManifestsUrl?: string;
|
||||
|
||||
// The query context to set if the user does not have one saved in local storage, defaults to {}
|
||||
defaultQueryContext?: Record<string, any>;
|
||||
|
||||
|
@ -104,7 +101,6 @@ QueryRunner.defaultQueryExecutor = (payload, isSql, cancelToken) => {
|
|||
|
||||
ReactDOM.render(
|
||||
React.createElement(ConsoleApplication, {
|
||||
exampleManifestsUrl: consoleConfig.exampleManifestsUrl,
|
||||
defaultQueryContext: consoleConfig.defaultQueryContext,
|
||||
mandatoryQueryContext: consoleConfig.mandatoryQueryContext,
|
||||
}),
|
||||
|
|
|
@ -36,7 +36,7 @@ import type {
|
|||
Transform,
|
||||
} from '../druid-models';
|
||||
import { inflateDimensionSpec, upgradeSpec } from '../druid-models';
|
||||
import { deepGet, filterMap, oneOf } from '../utils';
|
||||
import { deepGet, filterMap, nonEmptyArray, oneOf } from '../utils';
|
||||
|
||||
export function getSpecDatasourceName(spec: IngestionSpec): string {
|
||||
return deepGet(spec, 'spec.dataSchema.dataSource') || 'unknown_datasource';
|
||||
|
@ -86,6 +86,10 @@ export function convertSpecToSql(spec: any): QueryWithContext {
|
|||
|
||||
const rollup = deepGet(spec, 'spec.dataSchema.granularitySpec.rollup') ?? true;
|
||||
|
||||
if (nonEmptyArray(deepGet(spec, 'spec.dataSchema.dimensionsSpec.spatialDimensions'))) {
|
||||
throw new Error(`spatialDimensions are not currently supported in SQL-based ingestion`);
|
||||
}
|
||||
|
||||
const timestampSpec: TimestampSpec = deepGet(spec, 'spec.dataSchema.timestampSpec');
|
||||
if (!timestampSpec) throw new Error(`spec.dataSchema.timestampSpec is not defined`);
|
||||
|
||||
|
|
|
@ -0,0 +1,30 @@
|
|||
/*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
import { useEffect, useRef } from 'react';
|
||||
|
||||
export function useLastDefinedDeep<T>(cur: T | undefined): T | undefined {
|
||||
const last = useRef<T>();
|
||||
|
||||
useEffect(() => {
|
||||
if (typeof cur === 'undefined' || JSON.stringify(last.current) === JSON.stringify(cur)) return;
|
||||
last.current = cur;
|
||||
}, [cur]);
|
||||
|
||||
return typeof cur === 'undefined' ? last.current : cur;
|
||||
}
|
|
@ -278,6 +278,13 @@ export function filterMap<T, Q>(xs: readonly T[], f: (x: T, i: number) => Q | un
|
|||
return xs.map(f).filter((x: Q | undefined) => typeof x !== 'undefined') as Q[];
|
||||
}
|
||||
|
||||
export function findMap<T, Q>(
|
||||
xs: readonly T[],
|
||||
f: (x: T, i: number) => Q | undefined,
|
||||
): Q | undefined {
|
||||
return filterMap(xs, f)[0];
|
||||
}
|
||||
|
||||
export function compact<T>(xs: (T | undefined | false | null | '')[]): T[] {
|
||||
return xs.filter(Boolean) as T[];
|
||||
}
|
||||
|
|
|
@ -17,21 +17,66 @@
|
|||
*/
|
||||
|
||||
// Just to make sure we are in a test context. This line will cause trouble if this file is ever compiled into the main build
|
||||
import type { SampleHeaderAndRows } from './sampler';
|
||||
import type { SampleResponse } from './sampler';
|
||||
|
||||
expect(1).toEqual(1);
|
||||
expect(1).toEqual(1); // Just to make sure this file does not get included in the build by accident
|
||||
|
||||
export const EMPTY_SAMPLE: SampleResponse = {
|
||||
numRowsRead: 0,
|
||||
numRowsIndexed: 0,
|
||||
logicalDimensions: [],
|
||||
physicalDimensions: [],
|
||||
logicalSegmentSchema: [{ name: '__time', type: 'LONG' }],
|
||||
data: [],
|
||||
};
|
||||
|
||||
/*
|
||||
This data is the returned sample when ingested with:
|
||||
This data is the returned sample when sampling (from the timestamp stage):
|
||||
|
||||
{"timestamp":"2016-04-11T09:20:00Z","user":"Alice","followers":10,"spend":0,"id":"12232323","tags":null,"nums":[4]}
|
||||
{"timestamp":"2016-04-11T09:21:00Z","user":"Bob","followers":0,"spend":3,"id":"45345634","tags":["a"],"nums":[5,6]}
|
||||
{"timestamp":"2016-04-11T09:22:00Z","user":"Alice","followers":3,"spend":5.1,"id":"73534533","tags":["a","b"],"nums":[7,8]}
|
||||
*/
|
||||
|
||||
export const JSON_SAMPLE: SampleHeaderAndRows = {
|
||||
header: ['timestamp', 'user', 'followers', 'spend', 'id', 'tags', 'nums'],
|
||||
rows: [
|
||||
export const JSON_SAMPLE: SampleResponse = {
|
||||
numRowsRead: 3,
|
||||
numRowsIndexed: 3,
|
||||
logicalDimensions: [
|
||||
{ type: 'string', name: 'user', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{
|
||||
type: 'long',
|
||||
name: 'followers',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: false,
|
||||
},
|
||||
{ type: 'json', name: 'spend', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'string', name: 'id', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'json', name: 'tags', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'json', name: 'nums', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
],
|
||||
physicalDimensions: [
|
||||
{ type: 'auto', name: 'user', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{
|
||||
type: 'auto',
|
||||
name: 'followers',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: true,
|
||||
},
|
||||
{ type: 'auto', name: 'spend', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'auto', name: 'id', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'auto', name: 'tags', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'auto', name: 'nums', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
],
|
||||
logicalSegmentSchema: [
|
||||
{ name: '__time', type: 'LONG' },
|
||||
{ name: 'user', type: 'STRING' },
|
||||
{ name: 'followers', type: 'LONG' },
|
||||
{ name: 'spend', type: 'COMPLEX<json>' },
|
||||
{ name: 'id', type: 'STRING' },
|
||||
{ name: 'tags', type: 'ARRAY<STRING>' },
|
||||
{ name: 'nums', type: 'ARRAY<LONG>' },
|
||||
],
|
||||
data: [
|
||||
{
|
||||
input: {
|
||||
timestamp: '2016-04-11T09:20:00Z',
|
||||
|
@ -43,14 +88,13 @@ export const JSON_SAMPLE: SampleHeaderAndRows = {
|
|||
nums: [4],
|
||||
},
|
||||
parsed: {
|
||||
__time: 0,
|
||||
timestamp: '2016-04-11T09:20:00Z',
|
||||
__time: 1460366400000,
|
||||
user: 'Alice',
|
||||
followers: '10',
|
||||
spend: '0',
|
||||
followers: 10,
|
||||
spend: 0,
|
||||
id: '12232323',
|
||||
tags: null,
|
||||
nums: '4',
|
||||
nums: [4],
|
||||
},
|
||||
},
|
||||
{
|
||||
|
@ -64,14 +108,13 @@ export const JSON_SAMPLE: SampleHeaderAndRows = {
|
|||
nums: [5, 6],
|
||||
},
|
||||
parsed: {
|
||||
__time: 0,
|
||||
timestamp: '2016-04-11T09:21:00Z',
|
||||
__time: 1460366460000,
|
||||
user: 'Bob',
|
||||
followers: '0',
|
||||
spend: '3',
|
||||
followers: 0,
|
||||
spend: 3,
|
||||
id: '45345634',
|
||||
tags: 'a',
|
||||
nums: ['5', '6'],
|
||||
tags: ['a'],
|
||||
nums: [5, 6],
|
||||
},
|
||||
},
|
||||
{
|
||||
|
@ -85,14 +128,13 @@ export const JSON_SAMPLE: SampleHeaderAndRows = {
|
|||
nums: [7, 8],
|
||||
},
|
||||
parsed: {
|
||||
__time: 0,
|
||||
timestamp: '2016-04-11T09:22:00Z',
|
||||
__time: 1460366520000,
|
||||
user: 'Alice',
|
||||
followers: '3',
|
||||
spend: '5.1',
|
||||
followers: 3,
|
||||
spend: 5.1,
|
||||
id: '73534533',
|
||||
tags: ['a', 'b'],
|
||||
nums: ['7', '8'],
|
||||
nums: [7, 8],
|
||||
},
|
||||
},
|
||||
],
|
||||
|
@ -119,9 +161,45 @@ SELECT
|
|||
FROM test_data
|
||||
*/
|
||||
|
||||
export const CSV_SAMPLE: SampleHeaderAndRows = {
|
||||
header: ['timestamp', 'user', 'followers', 'spend', 'id', 'tags', 'nums'],
|
||||
rows: [
|
||||
export const CSV_SAMPLE: SampleResponse = {
|
||||
numRowsRead: 3,
|
||||
numRowsIndexed: 3,
|
||||
logicalDimensions: [
|
||||
{ type: 'string', name: 'user', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{
|
||||
type: 'string',
|
||||
name: 'followers',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: true,
|
||||
},
|
||||
{ type: 'string', name: 'spend', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'string', name: 'id', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'json', name: 'tags', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'json', name: 'nums', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
],
|
||||
physicalDimensions: [
|
||||
{ type: 'auto', name: 'user', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{
|
||||
type: 'auto',
|
||||
name: 'followers',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: true,
|
||||
},
|
||||
{ type: 'auto', name: 'spend', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'auto', name: 'id', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'auto', name: 'tags', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
{ type: 'auto', name: 'nums', multiValueHandling: 'SORTED_ARRAY', createBitmapIndex: true },
|
||||
],
|
||||
logicalSegmentSchema: [
|
||||
{ name: '__time', type: 'LONG' },
|
||||
{ name: 'user', type: 'STRING' },
|
||||
{ name: 'followers', type: 'STRING' },
|
||||
{ name: 'spend', type: 'STRING' },
|
||||
{ name: 'id', type: 'STRING' },
|
||||
{ name: 'tags', type: 'COMPLEX<json>' },
|
||||
{ name: 'nums', type: 'COMPLEX<json>' },
|
||||
],
|
||||
data: [
|
||||
{
|
||||
input: {
|
||||
timestamp: '2016-04-11T09:20:00.000Z',
|
||||
|
@ -133,8 +211,7 @@ export const CSV_SAMPLE: SampleHeaderAndRows = {
|
|||
nums: '4',
|
||||
},
|
||||
parsed: {
|
||||
__time: 0,
|
||||
timestamp: '2016-04-11T09:20:00.000Z',
|
||||
__time: 1460366400000,
|
||||
user: 'Alice',
|
||||
followers: '10',
|
||||
spend: '0',
|
||||
|
@ -154,8 +231,7 @@ export const CSV_SAMPLE: SampleHeaderAndRows = {
|
|||
nums: ['5', '6'],
|
||||
},
|
||||
parsed: {
|
||||
__time: 0,
|
||||
timestamp: '2016-04-11T09:21:00.000Z',
|
||||
__time: 1460366460000,
|
||||
user: 'Bob',
|
||||
followers: '0',
|
||||
spend: '3',
|
||||
|
@ -175,8 +251,7 @@ export const CSV_SAMPLE: SampleHeaderAndRows = {
|
|||
nums: ['7', '8'],
|
||||
},
|
||||
parsed: {
|
||||
__time: 0,
|
||||
timestamp: '2016-04-11T09:22:00.000Z',
|
||||
__time: 1460366520000,
|
||||
user: 'Alice',
|
||||
followers: '3',
|
||||
spend: '5.1',
|
||||
|
|
|
@ -0,0 +1,133 @@
|
|||
/*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
import type { SampleResponse } from './sampler';
|
||||
import { guessDimensionsFromSampleResponse } from './sampler';
|
||||
|
||||
describe('sampler', () => {
|
||||
describe('getInferredDimensionsFromSampleResponse', () => {
|
||||
const sampleResponse: SampleResponse = {
|
||||
numRowsRead: 20,
|
||||
numRowsIndexed: 20,
|
||||
logicalDimensions: [
|
||||
{
|
||||
type: 'long',
|
||||
name: 'isRobot',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: false,
|
||||
},
|
||||
{
|
||||
type: 'string',
|
||||
name: 'channel',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: true,
|
||||
},
|
||||
{
|
||||
type: 'string',
|
||||
name: 'flags',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: true,
|
||||
},
|
||||
{
|
||||
type: 'long',
|
||||
name: 'isUnpatrolled',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: false,
|
||||
},
|
||||
],
|
||||
physicalDimensions: [
|
||||
{
|
||||
type: 'json',
|
||||
name: 'isRobot',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: true,
|
||||
},
|
||||
{
|
||||
type: 'json',
|
||||
name: 'channel',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: true,
|
||||
},
|
||||
{
|
||||
type: 'json',
|
||||
name: 'flags',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: true,
|
||||
},
|
||||
{
|
||||
type: 'json',
|
||||
name: 'isUnpatrolled',
|
||||
multiValueHandling: 'SORTED_ARRAY',
|
||||
createBitmapIndex: true,
|
||||
},
|
||||
],
|
||||
logicalSegmentSchema: [
|
||||
{ name: '__time', type: 'LONG' },
|
||||
{ name: 'isRobot', type: 'LONG' },
|
||||
{ name: 'channel', type: 'STRING' },
|
||||
{ name: 'flags', type: 'STRING' },
|
||||
{ name: 'isUnpatrolled', type: 'LONG' },
|
||||
],
|
||||
data: [
|
||||
{
|
||||
input: {
|
||||
isRobot: true,
|
||||
channel: '#sv.wikipedia',
|
||||
timestamp: '2016-06-27T00:00:11.080Z',
|
||||
flags: 'NB',
|
||||
isUnpatrolled: false,
|
||||
},
|
||||
parsed: {
|
||||
__time: 1466985611080,
|
||||
isRobot: true,
|
||||
channel: '#sv.wikipedia',
|
||||
flags: 'NB',
|
||||
isUnpatrolled: false,
|
||||
},
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
it('works', () => {
|
||||
expect(guessDimensionsFromSampleResponse(sampleResponse)).toMatchInlineSnapshot(`
|
||||
Array [
|
||||
Object {
|
||||
"name": "isRobot",
|
||||
"type": "string",
|
||||
},
|
||||
Object {
|
||||
"createBitmapIndex": true,
|
||||
"multiValueHandling": "SORTED_ARRAY",
|
||||
"name": "channel",
|
||||
"type": "string",
|
||||
},
|
||||
Object {
|
||||
"createBitmapIndex": true,
|
||||
"multiValueHandling": "SORTED_ARRAY",
|
||||
"name": "flags",
|
||||
"type": "string",
|
||||
},
|
||||
Object {
|
||||
"name": "isUnpatrolled",
|
||||
"type": "string",
|
||||
},
|
||||
]
|
||||
`);
|
||||
});
|
||||
});
|
||||
});
|
|
@ -20,6 +20,7 @@ import { dedupe } from 'druid-query-toolkit';
|
|||
import * as JSONBig from 'json-bigint-native';
|
||||
|
||||
import type {
|
||||
DimensionSpec,
|
||||
DimensionsSpec,
|
||||
IngestionSpec,
|
||||
IngestionType,
|
||||
|
@ -32,21 +33,20 @@ import type {
|
|||
} from '../druid-models';
|
||||
import {
|
||||
getDimensionNamesFromTransforms,
|
||||
getDimensionSpecName,
|
||||
getSpecType,
|
||||
getTimestampSchema,
|
||||
isDruidSource,
|
||||
PLACEHOLDER_TIMESTAMP_SPEC,
|
||||
REINDEX_TIMESTAMP_SPEC,
|
||||
TIME_COLUMN,
|
||||
upgradeSpec,
|
||||
} from '../druid-models';
|
||||
import { Api } from '../singletons';
|
||||
|
||||
import { getDruidErrorMessage, queryDruidRune } from './druid-query';
|
||||
import { arrangeWithPrefixSuffix, EMPTY_ARRAY, filterMap } from './general';
|
||||
import { EMPTY_ARRAY, filterMap } from './general';
|
||||
import { deepGet, deepSet } from './object-change';
|
||||
|
||||
const SAMPLER_URL = `/druid/indexer/v1/sampler`;
|
||||
const BASE_SAMPLER_CONFIG: SamplerConfig = {
|
||||
numRows: 500,
|
||||
timeoutMs: 15000,
|
||||
|
@ -63,6 +63,38 @@ export interface SamplerConfig {
|
|||
|
||||
export interface SampleResponse {
|
||||
data: SampleEntry[];
|
||||
logicalSegmentSchema: { name: string; type: string }[];
|
||||
logicalDimensions: DimensionSpec[];
|
||||
physicalDimensions: DimensionSpec[];
|
||||
numRowsIndexed: number;
|
||||
numRowsRead: number;
|
||||
}
|
||||
|
||||
export function getHeaderNamesFromSampleResponse(
|
||||
sampleResponse: SampleResponse,
|
||||
ignoreTimeColumn = false,
|
||||
) {
|
||||
return filterMap(sampleResponse.logicalSegmentSchema, s =>
|
||||
ignoreTimeColumn && s.name === '__time' ? undefined : s.name,
|
||||
);
|
||||
}
|
||||
|
||||
export function guessDimensionsFromSampleResponse(sampleResponse: SampleResponse): DimensionSpec[] {
|
||||
const { logicalDimensions, physicalDimensions, data } = sampleResponse;
|
||||
return logicalDimensions.map(d => {
|
||||
// Boolean column are currently reported as "long" so let's turn them into "string"
|
||||
if (
|
||||
d.type === 'long' &&
|
||||
physicalDimensions.find(_ => _.name === d.name)?.type === 'json' &&
|
||||
typeof data[0]?.input?.[d.name] === 'boolean'
|
||||
) {
|
||||
return {
|
||||
name: d.name,
|
||||
type: 'string',
|
||||
};
|
||||
}
|
||||
return d;
|
||||
});
|
||||
}
|
||||
|
||||
export type CacheRows = Record<string, any>[];
|
||||
|
@ -81,17 +113,6 @@ export interface SampleEntry {
|
|||
error?: string;
|
||||
}
|
||||
|
||||
export interface SampleHeaderAndRows {
|
||||
header: string[];
|
||||
rows: SampleEntry[];
|
||||
}
|
||||
|
||||
export interface ExampleManifest {
|
||||
name: string;
|
||||
description: string;
|
||||
spec: any;
|
||||
}
|
||||
|
||||
export function getCacheRowsFromSampleResponse(sampleResponse: SampleResponse): CacheRows {
|
||||
return filterMap(sampleResponse.data, d => d.input).slice(0, 20);
|
||||
}
|
||||
|
@ -126,46 +147,6 @@ export function applyCache(sampleSpec: SampleSpec, cacheRows: CacheRows) {
|
|||
return sampleSpec;
|
||||
}
|
||||
|
||||
export interface HeaderFromSampleResponseOptions {
|
||||
sampleResponse: SampleResponse;
|
||||
ignoreTimeColumn?: boolean;
|
||||
columnOrder?: string[];
|
||||
suffixColumnOrder?: string[];
|
||||
useInput?: boolean;
|
||||
}
|
||||
|
||||
export function headerFromSampleResponse(options: HeaderFromSampleResponseOptions): string[] {
|
||||
const { sampleResponse, ignoreTimeColumn, columnOrder, suffixColumnOrder, useInput } = options;
|
||||
|
||||
const key = useInput ? 'input' : 'parsed';
|
||||
let columns = arrangeWithPrefixSuffix(
|
||||
dedupe(sampleResponse.data.flatMap(s => (s[key] ? Object.keys(s[key]!) : []))),
|
||||
columnOrder || [TIME_COLUMN],
|
||||
suffixColumnOrder || [],
|
||||
);
|
||||
|
||||
if (ignoreTimeColumn) {
|
||||
columns = columns.filter(c => c !== TIME_COLUMN);
|
||||
}
|
||||
|
||||
return columns;
|
||||
}
|
||||
|
||||
export interface HeaderAndRowsFromSampleResponseOptions extends HeaderFromSampleResponseOptions {
|
||||
parsedOnly?: boolean;
|
||||
}
|
||||
|
||||
export function headerAndRowsFromSampleResponse(
|
||||
options: HeaderAndRowsFromSampleResponseOptions,
|
||||
): SampleHeaderAndRows {
|
||||
const { sampleResponse, parsedOnly } = options;
|
||||
|
||||
return {
|
||||
header: headerFromSampleResponse(options),
|
||||
rows: parsedOnly ? sampleResponse.data.filter(d => d.parsed) : sampleResponse.data,
|
||||
};
|
||||
}
|
||||
|
||||
export async function getProxyOverlordModules(): Promise<string[]> {
|
||||
let statusResp: any;
|
||||
try {
|
||||
|
@ -185,7 +166,7 @@ export async function postToSampler(
|
|||
|
||||
let sampleResp: any;
|
||||
try {
|
||||
sampleResp = await Api.instance.post(`${SAMPLER_URL}?for=${forStr}`, sampleSpec);
|
||||
sampleResp = await Api.instance.post(`/druid/indexer/v1/sampler?for=${forStr}`, sampleSpec);
|
||||
} catch (e) {
|
||||
throw new Error(getDruidErrorMessage(e));
|
||||
}
|
||||
|
@ -229,6 +210,23 @@ function fixSamplerTypes(sampleSpec: SampleSpec): SampleSpec {
|
|||
return sampleSpec;
|
||||
}
|
||||
|
||||
const WHOLE_ROW_INPUT_FORMAT: InputFormat = {
|
||||
type: 'regex',
|
||||
pattern: '([\\s\\S]*)', // Match the entire line, every single character
|
||||
listDelimiter: '56616469-6de2-9da4-efb8-8f416e6e6965', // Just a UUID to disable the list delimiter, let's hope we do not see this UUID in the data
|
||||
columns: ['raw'],
|
||||
};
|
||||
|
||||
const KAFKA_SAMPLE_INPUT_FORMAT: InputFormat = {
|
||||
type: 'kafka',
|
||||
headerFormat: {
|
||||
type: 'string',
|
||||
encoding: 'UTF-8',
|
||||
},
|
||||
keyFormat: WHOLE_ROW_INPUT_FORMAT,
|
||||
valueFormat: WHOLE_ROW_INPUT_FORMAT,
|
||||
};
|
||||
|
||||
export async function sampleForConnect(
|
||||
spec: Partial<IngestionSpec>,
|
||||
sampleStrategy: SampleStrategy,
|
||||
|
@ -242,12 +240,11 @@ export async function sampleForConnect(
|
|||
|
||||
const reingestMode = isDruidSource(spec);
|
||||
if (!reingestMode) {
|
||||
ioConfig = deepSet(ioConfig, 'inputFormat', {
|
||||
type: 'regex',
|
||||
pattern: '([\\s\\S]*)', // Match the entire line, every single character
|
||||
listDelimiter: '56616469-6de2-9da4-efb8-8f416e6e6965', // Just a UUID to disable the list delimiter, let's hope we do not see this UUID in the data
|
||||
columns: ['raw'],
|
||||
});
|
||||
ioConfig = deepSet(
|
||||
ioConfig,
|
||||
'inputFormat',
|
||||
samplerType === 'kafka' ? KAFKA_SAMPLE_INPUT_FORMAT : WHOLE_ROW_INPUT_FORMAT,
|
||||
);
|
||||
}
|
||||
|
||||
const sampleSpec: SampleSpec = {
|
||||
|
@ -332,7 +329,9 @@ export async function sampleForParser(
|
|||
dataSchema: {
|
||||
dataSource: 'sample',
|
||||
timestampSpec: reingestMode ? REINDEX_TIMESTAMP_SPEC : PLACEHOLDER_TIMESTAMP_SPEC,
|
||||
dimensionsSpec: {},
|
||||
dimensionsSpec: {
|
||||
useSchemaDiscovery: true,
|
||||
},
|
||||
granularitySpec: {
|
||||
rollup: false,
|
||||
},
|
||||
|
@ -359,7 +358,9 @@ export async function sampleForTimestamp(
|
|||
ioConfig: deepGet(spec, 'spec.ioConfig'),
|
||||
dataSchema: {
|
||||
dataSource: 'sample',
|
||||
dimensionsSpec: {},
|
||||
dimensionsSpec: {
|
||||
useSchemaDiscovery: true,
|
||||
},
|
||||
timestampSpec: timestampSchema === 'column' ? PLACEHOLDER_TIMESTAMP_SPEC : timestampSpec,
|
||||
granularitySpec: {
|
||||
rollup: false,
|
||||
|
@ -380,7 +381,7 @@ export async function sampleForTimestamp(
|
|||
const transforms: Transform[] =
|
||||
deepGet(spec, 'spec.dataSchema.transformSpec.transforms') || EMPTY_ARRAY;
|
||||
|
||||
// If we are trying to parts a column then get a bit fancy:
|
||||
// If we are trying to parse a column then get a bit fancy:
|
||||
// Query the same sample again (same cache key)
|
||||
const sampleSpec: SampleSpec = {
|
||||
type: samplerType,
|
||||
|
@ -388,7 +389,9 @@ export async function sampleForTimestamp(
|
|||
ioConfig: deepGet(spec, 'spec.ioConfig'),
|
||||
dataSchema: {
|
||||
dataSource: 'sample',
|
||||
dimensionsSpec: {},
|
||||
dimensionsSpec: {
|
||||
useSchemaDiscovery: true,
|
||||
},
|
||||
timestampSpec,
|
||||
transformSpec: {
|
||||
transforms: transforms.filter(transform => transform.name === TIME_COLUMN),
|
||||
|
@ -430,8 +433,8 @@ export async function sampleForTransform(
|
|||
const timestampSpec: TimestampSpec = deepGet(spec, 'spec.dataSchema.timestampSpec');
|
||||
const transforms: Transform[] = deepGet(spec, 'spec.dataSchema.transformSpec.transforms') || [];
|
||||
|
||||
// Extra step to simulate auto detecting dimension with transforms
|
||||
let specialDimensionSpec: DimensionsSpec = {};
|
||||
// Extra step to simulate auto-detecting dimension with transforms
|
||||
let specialDimensionSpec: DimensionsSpec = { useSchemaDiscovery: true };
|
||||
if (transforms && transforms.length) {
|
||||
const sampleSpecHack: SampleSpec = {
|
||||
type: samplerType,
|
||||
|
@ -440,7 +443,9 @@ export async function sampleForTransform(
|
|||
dataSchema: {
|
||||
dataSource: 'sample',
|
||||
timestampSpec,
|
||||
dimensionsSpec: {},
|
||||
dimensionsSpec: {
|
||||
useSchemaDiscovery: true,
|
||||
},
|
||||
granularitySpec: {
|
||||
rollup: false,
|
||||
},
|
||||
|
@ -458,10 +463,10 @@ export async function sampleForTransform(
|
|||
specialDimensionSpec,
|
||||
'dimensions',
|
||||
dedupe(
|
||||
headerFromSampleResponse({
|
||||
sampleResponse: sampleResponseHack,
|
||||
ignoreTimeColumn: true,
|
||||
}).concat(getDimensionNamesFromTransforms(transforms)),
|
||||
(
|
||||
guessDimensionsFromSampleResponse(sampleResponseHack) as (DimensionSpec | string)[]
|
||||
).concat(getDimensionNamesFromTransforms(transforms)),
|
||||
getDimensionSpecName,
|
||||
),
|
||||
);
|
||||
}
|
||||
|
@ -497,8 +502,8 @@ export async function sampleForFilter(
|
|||
const transforms: Transform[] = deepGet(spec, 'spec.dataSchema.transformSpec.transforms') || [];
|
||||
const filter: any = deepGet(spec, 'spec.dataSchema.transformSpec.filter');
|
||||
|
||||
// Extra step to simulate auto detecting dimension with transforms
|
||||
let specialDimensionSpec: DimensionsSpec = {};
|
||||
// Extra step to simulate auto-detecting dimension with transforms
|
||||
let specialDimensionSpec: DimensionsSpec = { useSchemaDiscovery: true };
|
||||
if (transforms && transforms.length) {
|
||||
const sampleSpecHack: SampleSpec = {
|
||||
type: samplerType,
|
||||
|
@ -507,7 +512,9 @@ export async function sampleForFilter(
|
|||
dataSchema: {
|
||||
dataSource: 'sample',
|
||||
timestampSpec,
|
||||
dimensionsSpec: {},
|
||||
dimensionsSpec: {
|
||||
useSchemaDiscovery: true,
|
||||
},
|
||||
granularitySpec: {
|
||||
rollup: false,
|
||||
},
|
||||
|
@ -525,10 +532,9 @@ export async function sampleForFilter(
|
|||
specialDimensionSpec,
|
||||
'dimensions',
|
||||
dedupe(
|
||||
headerFromSampleResponse({
|
||||
sampleResponse: sampleResponseHack,
|
||||
ignoreTimeColumn: true,
|
||||
}).concat(getDimensionNamesFromTransforms(transforms)),
|
||||
getHeaderNamesFromSampleResponse(sampleResponseHack, true).concat(
|
||||
getDimensionNamesFromTransforms(transforms),
|
||||
),
|
||||
),
|
||||
);
|
||||
}
|
||||
|
@ -591,55 +597,3 @@ export async function sampleForSchema(
|
|||
|
||||
return postToSampler(applyCache(sampleSpec, cacheRows), 'schema');
|
||||
}
|
||||
|
||||
export async function sampleForExampleManifests(
|
||||
exampleManifestUrl: string,
|
||||
): Promise<ExampleManifest[]> {
|
||||
const exampleSpec: SampleSpec = {
|
||||
type: 'index_parallel',
|
||||
spec: {
|
||||
ioConfig: {
|
||||
type: 'index_parallel',
|
||||
inputSource: { type: 'http', uris: [exampleManifestUrl] },
|
||||
inputFormat: { type: 'tsv', findColumnsFromHeader: true },
|
||||
},
|
||||
dataSchema: {
|
||||
dataSource: 'sample',
|
||||
timestampSpec: {
|
||||
column: 'timestamp',
|
||||
missingValue: '2010-01-01T00:00:00Z',
|
||||
},
|
||||
dimensionsSpec: {},
|
||||
},
|
||||
},
|
||||
samplerConfig: { numRows: 50, timeoutMs: 10000 },
|
||||
};
|
||||
|
||||
const exampleData = await postToSampler(exampleSpec, 'example-manifest');
|
||||
|
||||
return filterMap(exampleData.data, datum => {
|
||||
const parsed = datum.parsed;
|
||||
if (!parsed) return;
|
||||
let { name, description, spec } = parsed;
|
||||
try {
|
||||
spec = JSON.parse(spec);
|
||||
} catch {
|
||||
return;
|
||||
}
|
||||
|
||||
if (
|
||||
typeof name === 'string' &&
|
||||
typeof description === 'string' &&
|
||||
spec &&
|
||||
typeof spec === 'object'
|
||||
) {
|
||||
return {
|
||||
name: parsed.name,
|
||||
description: parsed.description,
|
||||
spec: upgradeSpec(spec),
|
||||
};
|
||||
} else {
|
||||
return;
|
||||
}
|
||||
});
|
||||
}
|
||||
|
|
|
@ -18,7 +18,7 @@
|
|||
|
||||
import type { IngestionSpec } from '../druid-models';
|
||||
|
||||
import { applyCache, headerFromSampleResponse } from './sampler';
|
||||
import { applyCache } from './sampler';
|
||||
|
||||
describe('utils', () => {
|
||||
const ingestionSpec: IngestionSpec = {
|
||||
|
@ -52,20 +52,6 @@ describe('utils', () => {
|
|||
},
|
||||
};
|
||||
|
||||
// const cacheRows: CacheRows = [{ make: 'Honda', model: 'Civic' }, { make: 'BMW', model: 'M3' }];
|
||||
|
||||
it('spec-utils headerFromSampleResponse', () => {
|
||||
expect(
|
||||
headerFromSampleResponse({
|
||||
sampleResponse: { data: [{ input: { a: 1 }, parsed: { a: 1 } }] },
|
||||
}),
|
||||
).toMatchInlineSnapshot(`
|
||||
Array [
|
||||
"a",
|
||||
]
|
||||
`);
|
||||
});
|
||||
|
||||
it('spec-utils applyCache', () => {
|
||||
expect(
|
||||
applyCache(
|
||||
|
|
|
@ -25,9 +25,9 @@ describe('ExamplePicker', () => {
|
|||
it('matches snapshot', () => {
|
||||
const examplePicker = (
|
||||
<ExamplePicker
|
||||
exampleManifests={[
|
||||
{ name: 'Wikipedia', description: 'stuff stuff', spec: {} },
|
||||
{ name: 'Ex 2', description: 'stuff stuff', spec: {} },
|
||||
exampleSpecs={[
|
||||
{ name: 'Wikipedia', description: 'stuff stuff', spec: {} as any },
|
||||
{ name: 'Ex 2', description: 'stuff stuff', spec: {} as any },
|
||||
]}
|
||||
onSelectExample={() => {}}
|
||||
/>
|
||||
|
|
|
@ -20,15 +20,15 @@ import { Button, Callout, FormGroup, HTMLSelect, Intent } from '@blueprintjs/cor
|
|||
import { IconNames } from '@blueprintjs/icons';
|
||||
import React, { useState } from 'react';
|
||||
|
||||
import type { ExampleManifest } from '../../../utils/sampler';
|
||||
import type { ExampleSpec } from '../example-specs';
|
||||
|
||||
export interface ExamplePickerProps {
|
||||
exampleManifests: ExampleManifest[];
|
||||
onSelectExample: (exampleManifest: ExampleManifest) => void;
|
||||
exampleSpecs: ExampleSpec[];
|
||||
onSelectExample(exampleSpec: ExampleSpec): void;
|
||||
}
|
||||
|
||||
export const ExamplePicker = React.memo(function ExamplePicker(props: ExamplePickerProps) {
|
||||
const { exampleManifests, onSelectExample } = props;
|
||||
const { exampleSpecs, onSelectExample } = props;
|
||||
const [selectedIndex, setSelectedIndex] = useState(0);
|
||||
|
||||
return (
|
||||
|
@ -39,15 +39,15 @@ export const ExamplePicker = React.memo(function ExamplePicker(props: ExamplePic
|
|||
value={selectedIndex}
|
||||
onChange={e => setSelectedIndex(e.target.value as any)}
|
||||
>
|
||||
{exampleManifests.map((exampleManifest, i) => (
|
||||
{exampleSpecs.map((exampleSpec, i) => (
|
||||
<option key={i} value={i}>
|
||||
{exampleManifest.name}
|
||||
{exampleSpec.name}
|
||||
</option>
|
||||
))}
|
||||
</HTMLSelect>
|
||||
</FormGroup>
|
||||
<FormGroup>
|
||||
<Callout>{exampleManifests[selectedIndex].description}</Callout>
|
||||
<Callout>{exampleSpecs[selectedIndex].description}</Callout>
|
||||
</FormGroup>
|
||||
<FormGroup>
|
||||
<Button
|
||||
|
@ -55,7 +55,7 @@ export const ExamplePicker = React.memo(function ExamplePicker(props: ExamplePic
|
|||
rightIcon={IconNames.ARROW_RIGHT}
|
||||
intent={Intent.PRIMARY}
|
||||
onClick={() => {
|
||||
onSelectExample(exampleManifests[selectedIndex]);
|
||||
onSelectExample(exampleSpecs[selectedIndex]);
|
||||
}}
|
||||
/>
|
||||
</FormGroup>
|
||||
|
|
|
@ -0,0 +1,102 @@
|
|||
/*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
export interface ExampleSpec {
|
||||
name: string;
|
||||
description: string;
|
||||
spec: any;
|
||||
}
|
||||
|
||||
export const EXAMPLE_SPECS: ExampleSpec[] = [
|
||||
{
|
||||
name: 'Wikipedia Edits',
|
||||
description: 'Edits on Wikipedia from one day',
|
||||
spec: {
|
||||
type: 'index_parallel',
|
||||
spec: {
|
||||
ioConfig: {
|
||||
type: 'index_parallel',
|
||||
inputSource: {
|
||||
type: 'http',
|
||||
uris: ['https://druid.apache.org/data/wikipedia.json.gz'],
|
||||
},
|
||||
},
|
||||
dataSchema: {
|
||||
granularitySpec: {
|
||||
segmentGranularity: 'day',
|
||||
},
|
||||
},
|
||||
tuningConfig: {
|
||||
type: 'index_parallel',
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
{
|
||||
name: 'KoalasToTheMax one day',
|
||||
description: 'One day of flat events from KoalasToTheMax.com (JSON)',
|
||||
spec: {
|
||||
type: 'index_parallel',
|
||||
spec: {
|
||||
ioConfig: {
|
||||
type: 'index_parallel',
|
||||
inputSource: {
|
||||
type: 'http',
|
||||
uris: ['https://static.imply.io/example-data/kttm-v2/kttm-v2-2019-08-25.json.gz'],
|
||||
},
|
||||
},
|
||||
dataSchema: {
|
||||
dataSource: 'kttm1',
|
||||
granularitySpec: {
|
||||
segmentGranularity: 'day',
|
||||
},
|
||||
},
|
||||
tuningConfig: {
|
||||
type: 'index_parallel',
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
{
|
||||
name: 'KoalasToTheMax one day (nested)',
|
||||
description: 'One day of nested events from KoalasToTheMax.com (JSON)',
|
||||
spec: {
|
||||
type: 'index_parallel',
|
||||
spec: {
|
||||
ioConfig: {
|
||||
type: 'index_parallel',
|
||||
inputSource: {
|
||||
type: 'http',
|
||||
uris: [
|
||||
'https://static.imply.io/example-data/kttm-nested-v2/kttm-nested-v2-2019-08-25.json.gz',
|
||||
],
|
||||
},
|
||||
},
|
||||
dataSchema: {
|
||||
dataSource: 'kttm_nested1',
|
||||
granularitySpec: {
|
||||
segmentGranularity: 'day',
|
||||
},
|
||||
},
|
||||
tuningConfig: {
|
||||
type: 'index_parallel',
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
];
|
File diff suppressed because it is too large
Load Diff
|
@ -19,23 +19,15 @@
|
|||
import { render } from '@testing-library/react';
|
||||
import React from 'react';
|
||||
|
||||
import { JSON_SAMPLE } from '../../../utils/sampler.mock';
|
||||
|
||||
import { FilterTable } from './filter-table';
|
||||
|
||||
describe('FilterTable', () => {
|
||||
it('matches snapshot', () => {
|
||||
const sampleData = {
|
||||
header: ['c1'],
|
||||
rows: [
|
||||
{
|
||||
input: { c1: 'hello' },
|
||||
parsed: { c1: 'hello' },
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const filterTable = (
|
||||
<FilterTable
|
||||
sampleData={sampleData}
|
||||
sampleResponse={JSON_SAMPLE}
|
||||
columnFilter=""
|
||||
dimensionFilters={[]}
|
||||
selectedFilterName={undefined}
|
||||
|
|
|
@ -30,22 +30,23 @@ import {
|
|||
STANDARD_TABLE_PAGE_SIZE_OPTIONS,
|
||||
} from '../../../react-table';
|
||||
import { caseInsensitiveContains, filterMap } from '../../../utils';
|
||||
import type { SampleEntry, SampleHeaderAndRows } from '../../../utils/sampler';
|
||||
import type { SampleEntry, SampleResponse } from '../../../utils/sampler';
|
||||
import { getHeaderNamesFromSampleResponse } from '../../../utils/sampler';
|
||||
|
||||
import './filter-table.scss';
|
||||
|
||||
export function filterTableSelectedColumnName(
|
||||
sampleData: SampleHeaderAndRows,
|
||||
sampleResponse: SampleResponse,
|
||||
selectedFilter: Partial<DruidFilter> | undefined,
|
||||
): string | undefined {
|
||||
if (!selectedFilter) return;
|
||||
const selectedFilterName = selectedFilter.dimension;
|
||||
if (!sampleData.header.includes(selectedFilterName)) return;
|
||||
if (!getHeaderNamesFromSampleResponse(sampleResponse).includes(selectedFilterName)) return;
|
||||
return selectedFilterName;
|
||||
}
|
||||
|
||||
export interface FilterTableProps {
|
||||
sampleData: SampleHeaderAndRows;
|
||||
sampleResponse: SampleResponse;
|
||||
columnFilter: string;
|
||||
dimensionFilters: DruidFilter[];
|
||||
selectedFilterName: string | undefined;
|
||||
|
@ -53,17 +54,18 @@ export interface FilterTableProps {
|
|||
}
|
||||
|
||||
export const FilterTable = React.memo(function FilterTable(props: FilterTableProps) {
|
||||
const { sampleData, columnFilter, dimensionFilters, selectedFilterName, onFilterSelect } = props;
|
||||
const { sampleResponse, columnFilter, dimensionFilters, selectedFilterName, onFilterSelect } =
|
||||
props;
|
||||
|
||||
return (
|
||||
<ReactTable
|
||||
className={classNames('filter-table', DEFAULT_TABLE_CLASS_NAME)}
|
||||
data={sampleData.rows}
|
||||
data={sampleResponse.data}
|
||||
sortable={false}
|
||||
defaultPageSize={STANDARD_TABLE_PAGE_SIZE}
|
||||
pageSizeOptions={STANDARD_TABLE_PAGE_SIZE_OPTIONS}
|
||||
showPagination={sampleData.rows.length > STANDARD_TABLE_PAGE_SIZE}
|
||||
columns={filterMap(sampleData.header, (columnName, i) => {
|
||||
showPagination={sampleResponse.data.length > STANDARD_TABLE_PAGE_SIZE}
|
||||
columns={filterMap(getHeaderNamesFromSampleResponse(sampleResponse), (columnName, i) => {
|
||||
if (!caseInsensitiveContains(columnName, columnFilter)) return;
|
||||
const timestamp = columnName === '__time';
|
||||
const filterIndex = dimensionFilters.findIndex(f => getFilterDimension(f) === columnName);
|
||||
|
|
|
@ -57,13 +57,7 @@ export const ConnectMessage = React.memo(function ConnectMessage(props: ConnectM
|
|||
);
|
||||
});
|
||||
|
||||
export interface ParserMessageProps {
|
||||
canHaveNestedData: boolean;
|
||||
}
|
||||
|
||||
export const ParserMessage = React.memo(function ParserMessage(props: ParserMessageProps) {
|
||||
const { canHaveNestedData } = props;
|
||||
|
||||
export const ParserMessage = React.memo(function ParserMessage() {
|
||||
return (
|
||||
<FormGroup>
|
||||
<Callout>
|
||||
|
@ -71,24 +65,11 @@ export const ParserMessage = React.memo(function ParserMessage(props: ParserMess
|
|||
Druid needs to parse data as columns. Determine the format of your data and ensure that
|
||||
the columns are accurately parsed.
|
||||
</p>
|
||||
{canHaveNestedData && (
|
||||
<>
|
||||
<p>
|
||||
If you have nested data, you can ingest it into{' '}
|
||||
<ExternalLink href={`${getLink('DOCS')}/querying/nested-columns.html`}>
|
||||
COMPLEX<json>
|
||||
</ExternalLink>{' '}
|
||||
columns.
|
||||
If you have nested data, you can ingest it as{' '}
|
||||
<ExternalLink href={`${getLink('DOCS')}/querying/nested-columns.html`}>json</ExternalLink>{' '}
|
||||
dimensions.
|
||||
</p>
|
||||
<p>
|
||||
Alternatively, you can explicitly{' '}
|
||||
<ExternalLink href={`${getLink('DOCS')}/ingestion/index.html#flattenspec`}>
|
||||
flatten
|
||||
</ExternalLink>{' '}
|
||||
it here.
|
||||
</p>
|
||||
</>
|
||||
)}
|
||||
<LearnMore href={`${getLink('DOCS')}/ingestion/data-formats.html`} />
|
||||
</Callout>
|
||||
</FormGroup>
|
||||
|
|
|
@ -316,4 +316,8 @@ $actual-icon-height: 400px;
|
|||
width: 100%;
|
||||
height: 100% !important;
|
||||
}
|
||||
|
||||
.parse-metadata {
|
||||
border-top: 1px solid $gray1;
|
||||
}
|
||||
}
|
||||
|
|
|
@ -73,6 +73,7 @@ import {
|
|||
addTimestampTransform,
|
||||
adjustForceGuaranteedRollup,
|
||||
adjustId,
|
||||
BATCH_INPUT_FORMAT_FIELDS,
|
||||
cleanSpec,
|
||||
computeFlattenPathsForData,
|
||||
CONSTANT_TIMESTAMP_SPEC,
|
||||
|
@ -95,10 +96,10 @@ import {
|
|||
getRequiredModule,
|
||||
getRollup,
|
||||
getSecondaryPartitionRelatedFormFields,
|
||||
getSpecType,
|
||||
getTimestampExpressionFields,
|
||||
getTimestampSchema,
|
||||
getTuningFormFields,
|
||||
INPUT_FORMAT_FIELDS,
|
||||
inputFormatCanProduceNestedData,
|
||||
invalidIoConfig,
|
||||
invalidPartitionConfig,
|
||||
|
@ -108,6 +109,7 @@ import {
|
|||
issueWithIoConfig,
|
||||
issueWithSampleData,
|
||||
joinFilter,
|
||||
KAFKA_METADATA_INPUT_FORMAT_FIELDS,
|
||||
KNOWN_FILTER_TYPES,
|
||||
MAX_INLINE_DATA_LENGTH,
|
||||
METRIC_SPEC_FIELDS,
|
||||
|
@ -129,8 +131,10 @@ import { getLink } from '../../links';
|
|||
import { Api, AppToaster, UrlBaser } from '../../singletons';
|
||||
import {
|
||||
alphanumericCompare,
|
||||
compact,
|
||||
deepDelete,
|
||||
deepGet,
|
||||
deepMove,
|
||||
deepSet,
|
||||
deepSetMulti,
|
||||
EMPTY_ARRAY,
|
||||
|
@ -147,19 +151,17 @@ import {
|
|||
} from '../../utils';
|
||||
import type {
|
||||
CacheRows,
|
||||
ExampleManifest,
|
||||
SampleEntry,
|
||||
SampleHeaderAndRows,
|
||||
SampleResponse,
|
||||
SampleResponseWithExtraInfo,
|
||||
SampleStrategy,
|
||||
} from '../../utils/sampler';
|
||||
import {
|
||||
getCacheRowsFromSampleResponse,
|
||||
getHeaderNamesFromSampleResponse,
|
||||
getProxyOverlordModules,
|
||||
headerAndRowsFromSampleResponse,
|
||||
guessDimensionsFromSampleResponse,
|
||||
sampleForConnect,
|
||||
sampleForExampleManifests,
|
||||
sampleForFilter,
|
||||
sampleForParser,
|
||||
sampleForSchema,
|
||||
|
@ -168,6 +170,7 @@ import {
|
|||
} from '../../utils/sampler';
|
||||
|
||||
import { ExamplePicker } from './example-picker/example-picker';
|
||||
import { EXAMPLE_SPECS } from './example-specs';
|
||||
import { FilterTable, filterTableSelectedColumnName } from './filter-table/filter-table';
|
||||
import { FormEditor } from './form-editor/form-editor';
|
||||
import {
|
||||
|
@ -213,46 +216,74 @@ function showRawLine(line: SampleEntry): string {
|
|||
}
|
||||
|
||||
function showDruidLine(line: SampleEntry): string {
|
||||
if (!line.input) return 'Invalid row';
|
||||
return `Druid row: ${JSONBig.stringify(line.input)}`;
|
||||
if (!line.input) return 'Invalid druid row';
|
||||
return `[Druid row: ${JSONBig.stringify(line.input)}]`;
|
||||
}
|
||||
|
||||
function showKafkaLine(line: SampleEntry): string {
|
||||
const { input } = line;
|
||||
if (!input) return 'Invalid kafka row';
|
||||
return compact([
|
||||
`[ Kafka timestamp: ${input['kafka.timestamp']}`,
|
||||
...filterMap(Object.entries(input), ([k, v]) => {
|
||||
if (!k.startsWith('kafka.header.')) return;
|
||||
return ` Header: ${k.slice(13)}=${v}`;
|
||||
}),
|
||||
input['kafka.key'] ? ` Key: ${input['kafka.key']}` : undefined,
|
||||
` Payload: ${input.raw}`,
|
||||
']',
|
||||
]).join('\n');
|
||||
}
|
||||
|
||||
function showBlankLine(line: SampleEntry): string {
|
||||
return line.parsed ? `[Row: ${JSONBig.stringify(line.parsed)}]` : '[Binary data]';
|
||||
}
|
||||
|
||||
function formatSampleEntries(sampleEntries: SampleEntry[], isDruidSource: boolean): string {
|
||||
if (sampleEntries.length) {
|
||||
if (isDruidSource) {
|
||||
function formatSampleEntries(
|
||||
sampleEntries: SampleEntry[],
|
||||
druidSource: boolean,
|
||||
kafkaSource: boolean,
|
||||
): string {
|
||||
if (!sampleEntries.length) return 'No data returned from sampler';
|
||||
|
||||
if (druidSource) {
|
||||
return sampleEntries.map(showDruidLine).join('\n');
|
||||
}
|
||||
|
||||
if (kafkaSource) {
|
||||
return sampleEntries.map(showKafkaLine).join('\n');
|
||||
}
|
||||
|
||||
return (
|
||||
sampleEntries.every(l => !l.parsed)
|
||||
? sampleEntries.map(showBlankLine)
|
||||
: sampleEntries.map(showRawLine)
|
||||
).join('\n');
|
||||
} else {
|
||||
return 'No data returned from sampler';
|
||||
}
|
||||
}
|
||||
|
||||
function getTimestampSpec(headerAndRows: SampleHeaderAndRows | null): TimestampSpec {
|
||||
if (!headerAndRows) return CONSTANT_TIMESTAMP_SPEC;
|
||||
function getTimestampSpec(sampleResponse: SampleResponse | null): TimestampSpec {
|
||||
if (!sampleResponse) return CONSTANT_TIMESTAMP_SPEC;
|
||||
|
||||
const timestampSpecs = filterMap(headerAndRows.header, sampleHeader => {
|
||||
const timestampSpecs = filterMap(
|
||||
getHeaderNamesFromSampleResponse(sampleResponse),
|
||||
sampleHeader => {
|
||||
const possibleFormat = possibleDruidFormatForValues(
|
||||
filterMap(headerAndRows.rows, d => (d.parsed ? d.parsed[sampleHeader] : undefined)),
|
||||
filterMap(sampleResponse.data, d => (d.parsed ? d.parsed[sampleHeader] : undefined)),
|
||||
);
|
||||
if (!possibleFormat) return;
|
||||
return {
|
||||
column: sampleHeader,
|
||||
format: possibleFormat,
|
||||
};
|
||||
});
|
||||
},
|
||||
);
|
||||
|
||||
return (
|
||||
timestampSpecs.find(ts => /time/i.test(ts.column)) || // Use a suggestion that has time in the name if possible
|
||||
// Prefer a suggestion that has "time" in the name and is not a numeric format
|
||||
timestampSpecs.find(
|
||||
ts => /time/i.test(ts.column) && !NUMERIC_TIME_FORMATS.includes(ts.format),
|
||||
) ||
|
||||
timestampSpecs.find(ts => /time/i.test(ts.column)) || // Otherwise anything that has "time" in the name
|
||||
timestampSpecs.find(ts => !NUMERIC_TIME_FORMATS.includes(ts.format)) || // Use a suggestion that is not numeric
|
||||
timestampSpecs[0] || // Fall back to the first one
|
||||
CONSTANT_TIMESTAMP_SPEC // Ok, empty it is...
|
||||
|
@ -319,7 +350,6 @@ export interface LoadDataViewProps {
|
|||
mode: LoadDataViewMode;
|
||||
initSupervisorId?: string;
|
||||
initTaskId?: string;
|
||||
exampleManifestsUrl?: string;
|
||||
goToIngestion: (taskGroupId: string | undefined, openDialog?: string) => void;
|
||||
}
|
||||
|
||||
|
@ -342,7 +372,6 @@ export interface LoadDataViewState {
|
|||
// welcome
|
||||
overlordModules?: string[];
|
||||
selectedComboType?: IngestionComboTypeWithExtra;
|
||||
exampleManifests?: ExampleManifest[];
|
||||
|
||||
// general
|
||||
sampleStrategy: SampleStrategy;
|
||||
|
@ -354,30 +383,31 @@ export interface LoadDataViewState {
|
|||
inputQueryState: QueryState<SampleResponseWithExtraInfo>;
|
||||
|
||||
// for parser
|
||||
parserQueryState: QueryState<SampleHeaderAndRows>;
|
||||
parserQueryState: QueryState<SampleResponse>;
|
||||
|
||||
// for flatten
|
||||
selectedFlattenField?: SelectedIndex<FlattenField>;
|
||||
|
||||
// for timestamp
|
||||
timestampQueryState: QueryState<{
|
||||
headerAndRows: SampleHeaderAndRows;
|
||||
sampleResponse: SampleResponse;
|
||||
spec: Partial<IngestionSpec>;
|
||||
}>;
|
||||
|
||||
// for transform
|
||||
transformQueryState: QueryState<SampleHeaderAndRows>;
|
||||
transformQueryState: QueryState<SampleResponse>;
|
||||
selectedTransform?: SelectedIndex<Transform>;
|
||||
|
||||
// for filter
|
||||
filterQueryState: QueryState<SampleHeaderAndRows>;
|
||||
filterQueryState: QueryState<SampleResponse>;
|
||||
selectedFilter?: SelectedIndex<DruidFilter>;
|
||||
|
||||
// for schema
|
||||
schemaQueryState: QueryState<{
|
||||
headerAndRows: SampleHeaderAndRows;
|
||||
sampleResponse: SampleResponse;
|
||||
dimensions: (string | DimensionSpec)[] | undefined;
|
||||
metricsSpec: MetricSpec[] | undefined;
|
||||
definedDimensions: boolean;
|
||||
}>;
|
||||
selectedAutoDimension?: string;
|
||||
selectedDimensionSpec?: SelectedIndex<DimensionSpec>;
|
||||
|
@ -613,9 +643,6 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
const { step } = this.state;
|
||||
|
||||
switch (step) {
|
||||
case 'welcome':
|
||||
return this.queryForWelcome();
|
||||
|
||||
case 'connect':
|
||||
return this.queryForConnect(initRun);
|
||||
|
||||
|
@ -635,6 +662,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
return this.queryForSchema(initRun);
|
||||
|
||||
case 'loading':
|
||||
case 'welcome':
|
||||
case 'partition':
|
||||
case 'publish':
|
||||
case 'tuning':
|
||||
|
@ -774,25 +802,6 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
|
||||
// ==================================================================
|
||||
|
||||
async queryForWelcome() {
|
||||
const { exampleManifestsUrl } = this.props;
|
||||
if (!exampleManifestsUrl) return;
|
||||
|
||||
let exampleManifests: ExampleManifest[] | undefined;
|
||||
try {
|
||||
exampleManifests = await sampleForExampleManifests(exampleManifestsUrl);
|
||||
} catch (e) {
|
||||
this.setState({
|
||||
exampleManifests: undefined,
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
this.setState({
|
||||
exampleManifests,
|
||||
});
|
||||
}
|
||||
|
||||
renderIngestionCard(
|
||||
comboType: IngestionComboTypeWithExtra,
|
||||
disabled?: boolean,
|
||||
|
@ -831,9 +840,8 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
}
|
||||
|
||||
renderWelcomeStep() {
|
||||
const { mode, exampleManifestsUrl } = this.props;
|
||||
const { spec, exampleManifests } = this.state;
|
||||
const noExamples = Boolean(!exampleManifests || !exampleManifests.length);
|
||||
const { mode } = this.props;
|
||||
const { spec } = this.state;
|
||||
|
||||
const welcomeMessage = this.renderWelcomeStepMessage();
|
||||
return (
|
||||
|
@ -857,7 +865,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
{this.renderIngestionCard('index_parallel:http')}
|
||||
{this.renderIngestionCard('index_parallel:local')}
|
||||
{this.renderIngestionCard('index_parallel:inline')}
|
||||
{exampleManifestsUrl && this.renderIngestionCard('example', noExamples)}
|
||||
{this.renderIngestionCard('example')}
|
||||
</>
|
||||
)}
|
||||
{this.renderIngestionCard('other')}
|
||||
|
@ -879,7 +887,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
}
|
||||
|
||||
renderWelcomeStepMessage(): JSX.Element | undefined {
|
||||
const { selectedComboType, exampleManifests } = this.state;
|
||||
const { selectedComboType } = this.state;
|
||||
|
||||
if (!selectedComboType) {
|
||||
return <p>Please specify where your raw data is located.</p>;
|
||||
|
@ -969,11 +977,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
);
|
||||
|
||||
case 'example':
|
||||
if (exampleManifests && exampleManifests.length) {
|
||||
return; // Yield to example picker controls
|
||||
} else {
|
||||
return <p>Could not load examples.</p>;
|
||||
}
|
||||
|
||||
case 'other':
|
||||
return (
|
||||
|
@ -993,7 +997,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
|
||||
renderWelcomeStepControls(): JSX.Element | undefined {
|
||||
const { goToIngestion } = this.props;
|
||||
const { spec, selectedComboType, exampleManifests } = this.state;
|
||||
const { spec, selectedComboType } = this.state;
|
||||
|
||||
const issue = this.selectedIngestionTypeIssue();
|
||||
if (issue) return;
|
||||
|
@ -1063,12 +1067,11 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
);
|
||||
|
||||
case 'example':
|
||||
if (!exampleManifests) return;
|
||||
return (
|
||||
<ExamplePicker
|
||||
exampleManifests={exampleManifests}
|
||||
onSelectExample={exampleManifest => {
|
||||
this.updateSpec(exampleManifest.spec);
|
||||
exampleSpecs={EXAMPLE_SPECS}
|
||||
onSelectExample={exampleSpec => {
|
||||
this.updateSpec(exampleSpec.spec);
|
||||
this.updateStep('connect');
|
||||
}}
|
||||
/>
|
||||
|
@ -1211,6 +1214,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
const ioConfig: IoConfig = deepGet(spec, 'spec.ioConfig') || EMPTY_OBJECT;
|
||||
const inlineMode = deepGet(spec, 'spec.ioConfig.inputSource.type') === 'inline';
|
||||
const druidSource = isDruidSource(spec);
|
||||
const kafkaSource = getSpecType(spec) === 'kafka';
|
||||
|
||||
let mainFill: JSX.Element | string;
|
||||
if (inlineMode) {
|
||||
|
@ -1242,7 +1246,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
<TextArea
|
||||
className="raw-lines"
|
||||
readOnly
|
||||
value={formatSampleEntries(inputData, druidSource)}
|
||||
value={formatSampleEntries(inputData, druidSource, kafkaSource)}
|
||||
/>
|
||||
)}
|
||||
{inputQueryState.isLoading() && <Loader />}
|
||||
|
@ -1364,11 +1368,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
|
||||
this.updateSpec(fillDataSourceNameIfNeeded(newSpec));
|
||||
} else {
|
||||
const sampleLines = filterMap(inputQueryState.data.data, l =>
|
||||
l.input ? l.input.raw : undefined,
|
||||
);
|
||||
|
||||
const issue = issueWithSampleData(sampleLines, spec);
|
||||
const issue = issueWithSampleData(inputData, spec);
|
||||
if (issue) {
|
||||
AppToaster.show({
|
||||
icon: IconNames.WARNING_SIGN,
|
||||
|
@ -1379,9 +1379,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
return false;
|
||||
}
|
||||
|
||||
this.updateSpec(
|
||||
fillDataSourceNameIfNeeded(fillInputFormatIfNeeded(spec, sampleLines)),
|
||||
);
|
||||
this.updateSpec(fillDataSourceNameIfNeeded(fillInputFormatIfNeeded(spec, inputData)));
|
||||
}
|
||||
return true;
|
||||
},
|
||||
|
@ -1427,10 +1425,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
this.setState(({ parserQueryState }) => ({
|
||||
cacheRows: getCacheRowsFromSampleResponse(sampleResponse),
|
||||
parserQueryState: new QueryState({
|
||||
data: headerAndRowsFromSampleResponse({
|
||||
sampleResponse,
|
||||
ignoreTimeColumn: true,
|
||||
}),
|
||||
data: sampleResponse,
|
||||
lastData: parserQueryState.getSomeData(),
|
||||
}),
|
||||
}));
|
||||
|
@ -1473,7 +1468,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
</div>
|
||||
{data && (
|
||||
<ParseDataTable
|
||||
sampleData={data}
|
||||
sampleResponse={data}
|
||||
columnFilter={columnFilter}
|
||||
canFlatten={canHaveNestedData}
|
||||
flattenedColumnsOnly={specialColumnsOnly}
|
||||
|
@ -1492,31 +1487,85 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
let suggestedFlattenFields: FlattenField[] | undefined;
|
||||
if (canHaveNestedData && !flattenFields.length && parserQueryState.data) {
|
||||
suggestedFlattenFields = computeFlattenPathsForData(
|
||||
filterMap(parserQueryState.data.rows, r => r.input),
|
||||
filterMap(parserQueryState.data.data, r => r.input),
|
||||
'ignore-arrays',
|
||||
);
|
||||
}
|
||||
|
||||
const specType = getSpecType(spec);
|
||||
const inputFormatFields = isStreamingSpec(spec)
|
||||
? STREAMING_INPUT_FORMAT_FIELDS
|
||||
: INPUT_FORMAT_FIELDS;
|
||||
: BATCH_INPUT_FORMAT_FIELDS;
|
||||
|
||||
const normalInputAutoForm = (
|
||||
<AutoForm
|
||||
fields={inputFormatFields}
|
||||
model={inputFormat}
|
||||
onChange={p => this.updateSpecPreview(deepSet(spec, 'spec.ioConfig.inputFormat', p))}
|
||||
/>
|
||||
);
|
||||
|
||||
return (
|
||||
<>
|
||||
<div className="main">{mainFill}</div>
|
||||
<div className="control">
|
||||
<ParserMessage canHaveNestedData={canHaveNestedData} />
|
||||
<ParserMessage />
|
||||
{!selectedFlattenField && (
|
||||
<>
|
||||
{specType !== 'kafka' ? (
|
||||
normalInputAutoForm
|
||||
) : (
|
||||
<>
|
||||
{inputFormat?.type !== 'kafka' ? (
|
||||
normalInputAutoForm
|
||||
) : (
|
||||
<AutoForm
|
||||
fields={inputFormatFields}
|
||||
model={inputFormat?.valueFormat}
|
||||
onChange={p =>
|
||||
this.updateSpecPreview(
|
||||
deepSet(spec, 'spec.ioConfig.inputFormat.valueFormat', p),
|
||||
)
|
||||
}
|
||||
/>
|
||||
)}
|
||||
<FormGroup className="parse-metadata">
|
||||
<Switch
|
||||
label="Parse Kafka metadata (ts, headers, key)"
|
||||
checked={inputFormat?.type === 'kafka'}
|
||||
onChange={() => {
|
||||
this.updateSpecPreview(
|
||||
inputFormat?.type === 'kafka'
|
||||
? deepMove(
|
||||
spec,
|
||||
'spec.ioConfig.inputFormat.valueFormat',
|
||||
'spec.ioConfig.inputFormat',
|
||||
)
|
||||
: deepSet(spec, 'spec.ioConfig.inputFormat', {
|
||||
type: 'kafka',
|
||||
valueFormat: inputFormat,
|
||||
}),
|
||||
);
|
||||
}}
|
||||
/>
|
||||
</FormGroup>
|
||||
{inputFormat?.type === 'kafka' && (
|
||||
<AutoForm
|
||||
fields={KAFKA_METADATA_INPUT_FORMAT_FIELDS}
|
||||
model={inputFormat}
|
||||
onChange={p =>
|
||||
this.updateSpecPreview(deepSet(spec, 'spec.ioConfig.inputFormat', p))
|
||||
}
|
||||
/>
|
||||
)}
|
||||
</>
|
||||
)}
|
||||
{this.renderApplyButtonBar(
|
||||
parserQueryState,
|
||||
AutoForm.issueWithModel(inputFormat, inputFormatFields),
|
||||
AutoForm.issueWithModel(inputFormat, inputFormatFields) ||
|
||||
(inputFormat?.type === 'kafka'
|
||||
? AutoForm.issueWithModel(inputFormat, KAFKA_METADATA_INPUT_FORMAT_FIELDS)
|
||||
: undefined),
|
||||
)}
|
||||
</>
|
||||
)}
|
||||
|
@ -1668,9 +1717,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
this.setState(({ timestampQueryState }) => ({
|
||||
timestampQueryState: new QueryState({
|
||||
data: {
|
||||
headerAndRows: headerAndRowsFromSampleResponse({
|
||||
sampleResponse,
|
||||
}),
|
||||
spec,
|
||||
},
|
||||
lastData: timestampQueryState.getSomeData(),
|
||||
|
@ -1717,7 +1764,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
columnFilter={columnFilter}
|
||||
possibleTimestampColumnsOnly={specialColumnsOnly}
|
||||
selectedColumnName={parseTimeTableSelectedColumnName(
|
||||
data.headerAndRows,
|
||||
data.sampleResponse,
|
||||
timestampSpec,
|
||||
)}
|
||||
onTimestampColumnSelect={this.onTimestampColumnSelect}
|
||||
|
@ -1858,9 +1905,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
|
||||
this.setState(({ transformQueryState }) => ({
|
||||
transformQueryState: new QueryState({
|
||||
data: headerAndRowsFromSampleResponse({
|
||||
sampleResponse,
|
||||
}),
|
||||
data: sampleResponse,
|
||||
lastData: transformQueryState.getSomeData(),
|
||||
}),
|
||||
}));
|
||||
|
@ -1876,7 +1921,8 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
if (transformQueryState.isInit()) {
|
||||
mainFill = <CenterMessage>Please fill in the previous steps</CenterMessage>;
|
||||
} else {
|
||||
const data = transformQueryState.getSomeData();
|
||||
const sampleResponse = transformQueryState.getSomeData();
|
||||
|
||||
mainFill = (
|
||||
<div className="table-with-control">
|
||||
<div className="table-control">
|
||||
|
@ -1892,13 +1938,16 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
disabled={!transforms.length}
|
||||
/>
|
||||
</div>
|
||||
{data && (
|
||||
{sampleResponse && (
|
||||
<TransformTable
|
||||
sampleData={data}
|
||||
sampleResponse={sampleResponse}
|
||||
columnFilter={columnFilter}
|
||||
transformedColumnsOnly={specialColumnsOnly}
|
||||
transforms={transforms}
|
||||
selectedColumnName={transformTableSelectedColumnName(data, selectedTransform?.value)}
|
||||
selectedColumnName={transformTableSelectedColumnName(
|
||||
sampleResponse,
|
||||
selectedTransform?.value,
|
||||
)}
|
||||
onTransformSelect={this.onTransformSelect}
|
||||
/>
|
||||
)}
|
||||
|
@ -2045,10 +2094,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
if (sampleResponse.data.length) {
|
||||
this.setState(({ filterQueryState }) => ({
|
||||
filterQueryState: new QueryState({
|
||||
data: headerAndRowsFromSampleResponse({
|
||||
sampleResponse,
|
||||
parsedOnly: true,
|
||||
}),
|
||||
data: sampleResponse,
|
||||
lastData: filterQueryState.getSomeData(),
|
||||
}),
|
||||
}));
|
||||
|
@ -2067,15 +2113,10 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
return;
|
||||
}
|
||||
|
||||
const headerAndRowsNoFilter = headerAndRowsFromSampleResponse({
|
||||
sampleResponse: sampleResponseNoFilter,
|
||||
parsedOnly: true,
|
||||
});
|
||||
|
||||
this.setState(({ filterQueryState }) => ({
|
||||
// cacheRows: sampleResponseNoFilter.cacheKey,
|
||||
filterQueryState: new QueryState({
|
||||
data: deepSet(headerAndRowsNoFilter, 'rows', []),
|
||||
data: sampleResponseNoFilter,
|
||||
lastData: filterQueryState.getSomeData(),
|
||||
}),
|
||||
}));
|
||||
|
@ -2095,7 +2136,8 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
if (filterQueryState.isInit()) {
|
||||
mainFill = <CenterMessage>Please enter more details for the previous steps</CenterMessage>;
|
||||
} else {
|
||||
const data = filterQueryState.getSomeData();
|
||||
const filterQuery = filterQueryState.getSomeData();
|
||||
|
||||
mainFill = (
|
||||
<div className="table-with-control">
|
||||
<div className="table-control">
|
||||
|
@ -2105,12 +2147,12 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
placeholder="Search columns"
|
||||
/>
|
||||
</div>
|
||||
{data && (
|
||||
{filterQuery && (
|
||||
<FilterTable
|
||||
sampleData={data}
|
||||
sampleResponse={filterQuery}
|
||||
columnFilter={columnFilter}
|
||||
dimensionFilters={dimensionFilters}
|
||||
selectedFilterName={filterTableSelectedColumnName(data, selectedFilter?.value)}
|
||||
selectedFilterName={filterTableSelectedColumnName(filterQuery, selectedFilter?.value)}
|
||||
onFilterSelect={this.onFilterSelect}
|
||||
/>
|
||||
)}
|
||||
|
@ -2243,15 +2285,10 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
this.setState(({ schemaQueryState }) => ({
|
||||
schemaQueryState: new QueryState({
|
||||
data: {
|
||||
headerAndRows: headerAndRowsFromSampleResponse({
|
||||
sampleResponse,
|
||||
columnOrder: [TIME_COLUMN].concat(
|
||||
dimensions ? dimensions.map(getDimensionSpecName) : [],
|
||||
),
|
||||
suffixColumnOrder: metricsSpec ? metricsSpec.map(getMetricSpecName) : undefined,
|
||||
}),
|
||||
dimensions,
|
||||
dimensions: dimensions || guessDimensionsFromSampleResponse(sampleResponse),
|
||||
metricsSpec,
|
||||
definedDimensions: Boolean(dimensions),
|
||||
},
|
||||
lastData: schemaQueryState.getSomeData(),
|
||||
}),
|
||||
|
@ -2569,13 +2606,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
action={async () => {
|
||||
const sampleResponse = await sampleForTransform(spec, cacheRows);
|
||||
this.updateSpec(
|
||||
updateSchemaWithSample(
|
||||
spec,
|
||||
headerAndRowsFromSampleResponse({ sampleResponse }),
|
||||
getDimensionMode(spec),
|
||||
newRollup,
|
||||
true,
|
||||
),
|
||||
updateSchemaWithSample(spec, sampleResponse, getDimensionMode(spec), newRollup, true),
|
||||
);
|
||||
}}
|
||||
confirmButtonText={`Yes - ${newRollup ? 'enable' : 'disable'} rollup`}
|
||||
|
@ -2600,12 +2631,7 @@ export class LoadDataView extends React.PureComponent<LoadDataViewProps, LoadDat
|
|||
action={async () => {
|
||||
const sampleResponse = await sampleForTransform(spec, cacheRows);
|
||||
this.updateSpec(
|
||||
updateSchemaWithSample(
|
||||
spec,
|
||||
headerAndRowsFromSampleResponse({ sampleResponse }),
|
||||
newDimensionMode,
|
||||
getRollup(spec),
|
||||
),
|
||||
updateSchemaWithSample(spec, sampleResponse, newDimensionMode, getRollup(spec)),
|
||||
);
|
||||
}}
|
||||
confirmButtonText={`Yes - ${autoDetect ? 'auto detect' : 'explicitly set'} columns`}
|
||||
|
|
File diff suppressed because it is too large
Load Diff
|
@ -19,23 +19,15 @@
|
|||
import { render } from '@testing-library/react';
|
||||
import React from 'react';
|
||||
|
||||
import { JSON_SAMPLE } from '../../../utils/sampler.mock';
|
||||
|
||||
import { ParseDataTable } from './parse-data-table';
|
||||
|
||||
describe('ParseDataTable', () => {
|
||||
it('matches snapshot', () => {
|
||||
const sampleData = {
|
||||
header: ['c1'],
|
||||
rows: [
|
||||
{
|
||||
input: { c1: 'hello' },
|
||||
parsed: { c1: 'hello' },
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const parseDataTable = (
|
||||
<ParseDataTable
|
||||
sampleData={sampleData}
|
||||
sampleResponse={JSON_SAMPLE}
|
||||
columnFilter=""
|
||||
canFlatten={false}
|
||||
flattenedColumnsOnly={false}
|
||||
|
|
|
@ -30,12 +30,13 @@ import {
|
|||
STANDARD_TABLE_PAGE_SIZE_OPTIONS,
|
||||
} from '../../../react-table';
|
||||
import { caseInsensitiveContains, filterMap } from '../../../utils';
|
||||
import type { SampleEntry, SampleHeaderAndRows } from '../../../utils/sampler';
|
||||
import type { SampleEntry, SampleResponse } from '../../../utils/sampler';
|
||||
import { getHeaderNamesFromSampleResponse } from '../../../utils/sampler';
|
||||
|
||||
import './parse-data-table.scss';
|
||||
|
||||
export interface ParseDataTableProps {
|
||||
sampleData: SampleHeaderAndRows;
|
||||
sampleResponse: SampleResponse;
|
||||
columnFilter: string;
|
||||
canFlatten: boolean;
|
||||
flattenedColumnsOnly: boolean;
|
||||
|
@ -46,7 +47,7 @@ export interface ParseDataTableProps {
|
|||
|
||||
export const ParseDataTable = React.memo(function ParseDataTable(props: ParseDataTableProps) {
|
||||
const {
|
||||
sampleData,
|
||||
sampleResponse,
|
||||
columnFilter,
|
||||
canFlatten,
|
||||
flattenedColumnsOnly,
|
||||
|
@ -59,12 +60,14 @@ export const ParseDataTable = React.memo(function ParseDataTable(props: ParseDat
|
|||
return (
|
||||
<ReactTable
|
||||
className={classNames('parse-data-table', DEFAULT_TABLE_CLASS_NAME)}
|
||||
data={sampleData.rows}
|
||||
data={sampleResponse.data}
|
||||
sortable={false}
|
||||
defaultPageSize={STANDARD_TABLE_PAGE_SIZE}
|
||||
pageSizeOptions={STANDARD_TABLE_PAGE_SIZE_OPTIONS}
|
||||
showPagination={sampleData.rows.length > STANDARD_TABLE_PAGE_SIZE}
|
||||
columns={filterMap(sampleData.header, (columnName, i) => {
|
||||
showPagination={sampleResponse.data.length > STANDARD_TABLE_PAGE_SIZE}
|
||||
columns={filterMap(
|
||||
getHeaderNamesFromSampleResponse(sampleResponse, true),
|
||||
(columnName, i) => {
|
||||
if (!caseInsensitiveContains(columnName, columnFilter)) return;
|
||||
const flattenFieldIndex = flattenFields.findIndex(f => f.name === columnName);
|
||||
if (flattenFieldIndex === -1 && flattenedColumnsOnly) return;
|
||||
|
@ -97,7 +100,8 @@ export const ParseDataTable = React.memo(function ParseDataTable(props: ParseDat
|
|||
flattened: flattenField,
|
||||
}),
|
||||
};
|
||||
})}
|
||||
},
|
||||
)}
|
||||
SubComponent={rowInfo => {
|
||||
const { input, error } = rowInfo.original;
|
||||
const inputStr = JSONBig.stringify(input, undefined, 2);
|
||||
|
|
File diff suppressed because it is too large
Load Diff
|
@ -22,21 +22,12 @@ import React from 'react';
|
|||
import type { IngestionSpec } from '../../../druid-models';
|
||||
import { PLACEHOLDER_TIMESTAMP_SPEC } from '../../../druid-models';
|
||||
import { deepSet } from '../../../utils';
|
||||
import { JSON_SAMPLE } from '../../../utils/sampler.mock';
|
||||
|
||||
import { ParseTimeTable } from './parse-time-table';
|
||||
|
||||
describe('ParseTimeTable', () => {
|
||||
it('matches snapshot', () => {
|
||||
const sampleData = {
|
||||
header: ['c1'],
|
||||
rows: [
|
||||
{
|
||||
input: { c1: 'hello' },
|
||||
parsed: { c1: 'hello' },
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const spec = deepSet(
|
||||
{} as IngestionSpec,
|
||||
'spec.dataSchema.timestampSpec',
|
||||
|
@ -46,7 +37,7 @@ describe('ParseTimeTable', () => {
|
|||
const parseTimeTable = (
|
||||
<ParseTimeTable
|
||||
sampleBundle={{
|
||||
headerAndRows: sampleData,
|
||||
sampleResponse: JSON_SAMPLE,
|
||||
spec,
|
||||
}}
|
||||
columnFilter=""
|
||||
|
|
|
@ -34,23 +34,29 @@ import {
|
|||
STANDARD_TABLE_PAGE_SIZE_OPTIONS,
|
||||
} from '../../../react-table';
|
||||
import { caseInsensitiveContains, filterMap } from '../../../utils';
|
||||
import type { SampleEntry, SampleHeaderAndRows } from '../../../utils/sampler';
|
||||
import type { SampleEntry, SampleResponse } from '../../../utils/sampler';
|
||||
import { getHeaderNamesFromSampleResponse } from '../../../utils/sampler';
|
||||
|
||||
import './parse-time-table.scss';
|
||||
|
||||
export function parseTimeTableSelectedColumnName(
|
||||
sampleData: SampleHeaderAndRows,
|
||||
sampleResponse: SampleResponse,
|
||||
timestampSpec: TimestampSpec | undefined,
|
||||
): string | undefined {
|
||||
if (!timestampSpec) return;
|
||||
const timestampColumn = timestampSpec.column;
|
||||
if (!timestampColumn || !sampleData.header.includes(timestampColumn)) return;
|
||||
if (
|
||||
!timestampColumn ||
|
||||
!getHeaderNamesFromSampleResponse(sampleResponse).includes(timestampColumn)
|
||||
) {
|
||||
return;
|
||||
}
|
||||
return timestampColumn;
|
||||
}
|
||||
|
||||
export interface ParseTimeTableProps {
|
||||
sampleBundle: {
|
||||
headerAndRows: SampleHeaderAndRows;
|
||||
sampleResponse: SampleResponse;
|
||||
spec: Partial<IngestionSpec>;
|
||||
};
|
||||
columnFilter: string;
|
||||
|
@ -67,28 +73,26 @@ export const ParseTimeTable = React.memo(function ParseTimeTable(props: ParseTim
|
|||
selectedColumnName,
|
||||
onTimestampColumnSelect,
|
||||
} = props;
|
||||
const { headerAndRows, spec } = sampleBundle;
|
||||
const { sampleResponse, spec } = sampleBundle;
|
||||
const timestampSpecColumn = getTimestampSpecColumnFromSpec(spec);
|
||||
const timestampDetail = getTimestampDetailFromSpec(spec);
|
||||
|
||||
return (
|
||||
<ReactTable
|
||||
className={classNames('parse-time-table', DEFAULT_TABLE_CLASS_NAME)}
|
||||
data={headerAndRows.rows}
|
||||
data={sampleResponse.data}
|
||||
sortable={false}
|
||||
defaultPageSize={STANDARD_TABLE_PAGE_SIZE}
|
||||
pageSizeOptions={STANDARD_TABLE_PAGE_SIZE_OPTIONS}
|
||||
showPagination={headerAndRows.rows.length > STANDARD_TABLE_PAGE_SIZE}
|
||||
columns={filterMap(
|
||||
headerAndRows.header.length ? headerAndRows.header : ['__error__'],
|
||||
(columnName, i) => {
|
||||
showPagination={sampleResponse.data.length > STANDARD_TABLE_PAGE_SIZE}
|
||||
columns={filterMap(getHeaderNamesFromSampleResponse(sampleResponse), (columnName, i) => {
|
||||
const isTimestamp = columnName === '__time';
|
||||
if (!isTimestamp && !caseInsensitiveContains(columnName, columnFilter)) return;
|
||||
const used = timestampSpecColumn === columnName;
|
||||
const possibleFormat = isTimestamp
|
||||
? null
|
||||
: possibleDruidFormatForValues(
|
||||
filterMap(headerAndRows.rows, d => (d.parsed ? d.parsed[columnName] : undefined)),
|
||||
filterMap(sampleResponse.data, d => (d.parsed ? d.parsed[columnName] : undefined)),
|
||||
);
|
||||
if (possibleTimestampColumnsOnly && !isTimestamp && !possibleFormat) return;
|
||||
|
||||
|
@ -135,8 +139,7 @@ export const ParseTimeTable = React.memo(function ParseTimeTable(props: ParseTim
|
|||
width: isTimestamp ? 200 : 140,
|
||||
resizable: !isTimestamp,
|
||||
};
|
||||
},
|
||||
)}
|
||||
})}
|
||||
/>
|
||||
);
|
||||
});
|
||||
|
|
File diff suppressed because it is too large
Load Diff
|
@ -19,26 +19,19 @@
|
|||
import { render } from '@testing-library/react';
|
||||
import React from 'react';
|
||||
|
||||
import { JSON_SAMPLE } from '../../../utils/sampler.mock';
|
||||
|
||||
import { SchemaTable } from './schema-table';
|
||||
|
||||
describe('SchemaTable', () => {
|
||||
it('matches snapshot', () => {
|
||||
const sampleData = {
|
||||
header: ['c1'],
|
||||
rows: [
|
||||
{
|
||||
input: { c1: 'hello' },
|
||||
parsed: { c1: 'hello' },
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const schemaTable = (
|
||||
<SchemaTable
|
||||
sampleBundle={{
|
||||
headerAndRows: sampleData,
|
||||
sampleResponse: JSON_SAMPLE,
|
||||
dimensions: [],
|
||||
metricsSpec: [],
|
||||
definedDimensions: false,
|
||||
}}
|
||||
columnFilter=""
|
||||
selectedAutoDimension={undefined}
|
||||
|
|
|
@ -35,15 +35,17 @@ import {
|
|||
STANDARD_TABLE_PAGE_SIZE_OPTIONS,
|
||||
} from '../../../react-table';
|
||||
import { caseInsensitiveContains, filterMap } from '../../../utils';
|
||||
import type { SampleEntry, SampleHeaderAndRows } from '../../../utils/sampler';
|
||||
import type { SampleEntry, SampleResponse } from '../../../utils/sampler';
|
||||
import { getHeaderNamesFromSampleResponse } from '../../../utils/sampler';
|
||||
|
||||
import './schema-table.scss';
|
||||
|
||||
export interface SchemaTableProps {
|
||||
sampleBundle: {
|
||||
headerAndRows: SampleHeaderAndRows;
|
||||
sampleResponse: SampleResponse;
|
||||
dimensions: (string | DimensionSpec)[] | undefined;
|
||||
metricsSpec: MetricSpec[] | undefined;
|
||||
definedDimensions: boolean;
|
||||
};
|
||||
columnFilter: string;
|
||||
selectedAutoDimension: string | undefined;
|
||||
|
@ -65,17 +67,17 @@ export const SchemaTable = React.memo(function SchemaTable(props: SchemaTablePro
|
|||
onDimensionSelect,
|
||||
onMetricSelect,
|
||||
} = props;
|
||||
const { headerAndRows, dimensions, metricsSpec } = sampleBundle;
|
||||
const { sampleResponse, dimensions, metricsSpec, definedDimensions } = sampleBundle;
|
||||
|
||||
return (
|
||||
<ReactTable
|
||||
className={classNames('schema-table', DEFAULT_TABLE_CLASS_NAME)}
|
||||
data={headerAndRows.rows}
|
||||
data={sampleResponse.data}
|
||||
sortable={false}
|
||||
defaultPageSize={STANDARD_TABLE_PAGE_SIZE}
|
||||
pageSizeOptions={STANDARD_TABLE_PAGE_SIZE_OPTIONS}
|
||||
showPagination={headerAndRows.rows.length > STANDARD_TABLE_PAGE_SIZE}
|
||||
columns={filterMap(headerAndRows.header, (columnName, i) => {
|
||||
showPagination={sampleResponse.data.length > STANDARD_TABLE_PAGE_SIZE}
|
||||
columns={filterMap(getHeaderNamesFromSampleResponse(sampleResponse), (columnName, i) => {
|
||||
if (!caseInsensitiveContains(columnName, columnFilter)) return;
|
||||
|
||||
const metricSpecIndex = metricsSpec
|
||||
|
@ -130,7 +132,7 @@ export const SchemaTable = React.memo(function SchemaTable(props: SchemaTablePro
|
|||
onClick={() => {
|
||||
if (isTimestamp) return;
|
||||
|
||||
if (dimensionSpec) {
|
||||
if (definedDimensions && dimensionSpec) {
|
||||
onDimensionSelect(inflateDimensionSpec(dimensionSpec), dimensionSpecIndex);
|
||||
} else {
|
||||
onAutoDimensionSelect(columnName);
|
||||
|
@ -139,7 +141,7 @@ export const SchemaTable = React.memo(function SchemaTable(props: SchemaTablePro
|
|||
>
|
||||
<div className="column-name">{columnName}</div>
|
||||
<div className="column-detail">
|
||||
{isTimestamp ? 'long (time column)' : dimensionSpecType || 'string (auto)'}
|
||||
{isTimestamp ? 'long (time column)' : dimensionSpecType || '(auto)'}
|
||||
</div>
|
||||
</div>
|
||||
),
|
||||
|
|
File diff suppressed because it is too large
Load Diff
|
@ -19,23 +19,15 @@
|
|||
import { render } from '@testing-library/react';
|
||||
import React from 'react';
|
||||
|
||||
import { JSON_SAMPLE } from '../../../utils/sampler.mock';
|
||||
|
||||
import { TransformTable } from './transform-table';
|
||||
|
||||
describe('TransformTable', () => {
|
||||
it('matches snapshot', () => {
|
||||
const sampleData = {
|
||||
header: ['c1'],
|
||||
rows: [
|
||||
{
|
||||
input: { c1: 'hello' },
|
||||
parsed: { c1: 'hello' },
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const transformTable = (
|
||||
<TransformTable
|
||||
sampleData={sampleData}
|
||||
sampleResponse={JSON_SAMPLE}
|
||||
columnFilter=""
|
||||
transformedColumnsOnly={false}
|
||||
transforms={[]}
|
||||
|
|
|
@ -30,22 +30,28 @@ import {
|
|||
} from '../../../react-table';
|
||||
import { caseInsensitiveContains, filterMap } from '../../../utils';
|
||||
import { escapeColumnName } from '../../../utils/druid-expression';
|
||||
import type { SampleEntry, SampleHeaderAndRows } from '../../../utils/sampler';
|
||||
import type { SampleEntry, SampleResponse } from '../../../utils/sampler';
|
||||
import { getHeaderNamesFromSampleResponse } from '../../../utils/sampler';
|
||||
|
||||
import './transform-table.scss';
|
||||
|
||||
export function transformTableSelectedColumnName(
|
||||
sampleData: SampleHeaderAndRows,
|
||||
sampleResponse: SampleResponse,
|
||||
selectedTransform: Partial<Transform> | undefined,
|
||||
): string | undefined {
|
||||
if (!selectedTransform) return;
|
||||
const selectedTransformName = selectedTransform.name;
|
||||
if (selectedTransformName && !sampleData.header.includes(selectedTransformName)) return;
|
||||
if (
|
||||
selectedTransformName &&
|
||||
!getHeaderNamesFromSampleResponse(sampleResponse).includes(selectedTransformName)
|
||||
) {
|
||||
return;
|
||||
}
|
||||
return selectedTransformName;
|
||||
}
|
||||
|
||||
export interface TransformTableProps {
|
||||
sampleData: SampleHeaderAndRows;
|
||||
sampleResponse: SampleResponse;
|
||||
columnFilter: string;
|
||||
transformedColumnsOnly: boolean;
|
||||
transforms: Transform[];
|
||||
|
@ -55,7 +61,7 @@ export interface TransformTableProps {
|
|||
|
||||
export const TransformTable = React.memo(function TransformTable(props: TransformTableProps) {
|
||||
const {
|
||||
sampleData,
|
||||
sampleResponse,
|
||||
columnFilter,
|
||||
transformedColumnsOnly,
|
||||
transforms,
|
||||
|
@ -66,12 +72,12 @@ export const TransformTable = React.memo(function TransformTable(props: Transfor
|
|||
return (
|
||||
<ReactTable
|
||||
className={classNames('transform-table', DEFAULT_TABLE_CLASS_NAME)}
|
||||
data={sampleData.rows}
|
||||
data={sampleResponse.data}
|
||||
sortable={false}
|
||||
defaultPageSize={STANDARD_TABLE_PAGE_SIZE}
|
||||
pageSizeOptions={STANDARD_TABLE_PAGE_SIZE_OPTIONS}
|
||||
showPagination={sampleData.rows.length > STANDARD_TABLE_PAGE_SIZE}
|
||||
columns={filterMap(sampleData.header, (columnName, i) => {
|
||||
showPagination={sampleResponse.data.length > STANDARD_TABLE_PAGE_SIZE}
|
||||
columns={filterMap(getHeaderNamesFromSampleResponse(sampleResponse), (columnName, i) => {
|
||||
if (!caseInsensitiveContains(columnName, columnFilter)) return;
|
||||
const timestamp = columnName === '__time';
|
||||
const transformIndex = transforms.findIndex(f => f.name === columnName);
|
||||
|
|
|
@ -32,21 +32,29 @@ import { IconNames } from '@blueprintjs/icons';
|
|||
import { Popover2 } from '@blueprintjs/popover2';
|
||||
import classNames from 'classnames';
|
||||
import { select, selectAll } from 'd3-selection';
|
||||
import type { QueryResult } from 'druid-query-toolkit';
|
||||
import { C, F, QueryRunner, SqlExpression, SqlQuery } from 'druid-query-toolkit';
|
||||
import {
|
||||
C,
|
||||
Column,
|
||||
F,
|
||||
QueryResult,
|
||||
QueryRunner,
|
||||
SqlExpression,
|
||||
SqlQuery,
|
||||
SqlType,
|
||||
} from 'druid-query-toolkit';
|
||||
import React, { useCallback, useEffect, useLayoutEffect, useMemo, useRef, useState } from 'react';
|
||||
|
||||
import { ClearableInput, LearnMore, Loader } from '../../../components';
|
||||
import { AsyncActionDialog } from '../../../dialogs';
|
||||
import type { Execution, IngestQueryPattern } from '../../../druid-models';
|
||||
import type { Execution, ExternalConfig, IngestQueryPattern } from '../../../druid-models';
|
||||
import {
|
||||
changeQueryPatternExpression,
|
||||
externalConfigToTableExpression,
|
||||
fitIngestQueryPattern,
|
||||
getDestinationMode,
|
||||
getQueryPatternExpression,
|
||||
getQueryPatternExpressionType,
|
||||
ingestQueryPatternToQuery,
|
||||
PLACEHOLDER_TIMESTAMP_SPEC,
|
||||
possibleDruidFormatForValues,
|
||||
TIME_COLUMN,
|
||||
WorkbenchQueryPart,
|
||||
|
@ -57,6 +65,7 @@ import {
|
|||
submitTaskQuery,
|
||||
} from '../../../helpers';
|
||||
import { useLastDefined, usePermanentCallback, useQueryManager } from '../../../hooks';
|
||||
import { useLastDefinedDeep } from '../../../hooks/use-last-defined-deep';
|
||||
import { getLink } from '../../../links';
|
||||
import { AppToaster } from '../../../singletons';
|
||||
import type { QueryAction } from '../../../utils';
|
||||
|
@ -64,6 +73,7 @@ import {
|
|||
caseInsensitiveContains,
|
||||
change,
|
||||
dataTypeToIcon,
|
||||
deepSet,
|
||||
DruidError,
|
||||
filterMap,
|
||||
oneOf,
|
||||
|
@ -74,6 +84,7 @@ import {
|
|||
wait,
|
||||
without,
|
||||
} from '../../../utils';
|
||||
import { postToSampler } from '../../../utils/sampler';
|
||||
import { FlexibleQueryInput } from '../../workbench-view/flexible-query-input/flexible-query-input';
|
||||
import { ColumnActions } from '../column-actions/column-actions';
|
||||
import { ColumnEditor } from '../column-editor/column-editor';
|
||||
|
@ -375,28 +386,67 @@ export const SchemaStep = function SchemaStep(props: SchemaStepProps) {
|
|||
},
|
||||
});
|
||||
|
||||
const sampleQueryString = useLastDefined(
|
||||
const sampleExternalConfig = useLastDefinedDeep(
|
||||
ingestQueryPattern && mode !== 'sql' // Only sample the data if we are not in the SQL tab live editing the SQL
|
||||
? SqlQuery.create(
|
||||
externalConfigToTableExpression(ingestQueryPattern.mainExternalConfig),
|
||||
).toString()
|
||||
? ingestQueryPattern.mainExternalConfig
|
||||
: undefined,
|
||||
);
|
||||
|
||||
const [sampleState] = useQueryManager<string, QueryResult, Execution>({
|
||||
query: sampleQueryString,
|
||||
processQuery: async (sampleQueryString, cancelToken) => {
|
||||
return extractResult(
|
||||
await submitTaskQuery({
|
||||
query: sampleQueryString,
|
||||
context: {
|
||||
sqlOuterLimit: 50,
|
||||
const [sampleState] = useQueryManager<ExternalConfig, QueryResult, Execution>({
|
||||
query: sampleExternalConfig,
|
||||
processQuery: async sampleExternalConfig => {
|
||||
const sampleResponse = await postToSampler(
|
||||
{
|
||||
type: 'index_parallel',
|
||||
spec: {
|
||||
ioConfig: {
|
||||
type: 'index_parallel',
|
||||
inputSource: sampleExternalConfig.inputSource,
|
||||
inputFormat: deepSet(sampleExternalConfig.inputFormat, 'keepNullColumns', true),
|
||||
},
|
||||
cancelToken,
|
||||
dataSchema: {
|
||||
dataSource: 'sample',
|
||||
timestampSpec: PLACEHOLDER_TIMESTAMP_SPEC,
|
||||
dimensionsSpec: {
|
||||
dimensions: sampleExternalConfig.signature.map(s => {
|
||||
const t = s.columnType.getNativeType();
|
||||
return {
|
||||
name: s.getColumnName(),
|
||||
type: t === 'COMPLEX<json>' ? 'json' : t,
|
||||
};
|
||||
}),
|
||||
);
|
||||
},
|
||||
backgroundStatusCheck: executionBackgroundResultStatusCheck,
|
||||
granularitySpec: {
|
||||
rollup: false,
|
||||
},
|
||||
},
|
||||
},
|
||||
samplerConfig: {
|
||||
numRows: 50,
|
||||
timeoutMs: 15000,
|
||||
},
|
||||
},
|
||||
'sample',
|
||||
);
|
||||
|
||||
const columns = filterMap(sampleResponse.logicalSegmentSchema, ({ name, type }) => {
|
||||
if (name === '__time') return;
|
||||
return new Column({
|
||||
name,
|
||||
nativeType: type,
|
||||
sqlType: SqlType.fromNativeType(type).toString(),
|
||||
});
|
||||
});
|
||||
|
||||
return new QueryResult({
|
||||
header: columns,
|
||||
rows: filterMap(sampleResponse.data, r => {
|
||||
const { parsed } = r;
|
||||
if (!parsed) return;
|
||||
return columns.map(({ name }) => parsed[name]);
|
||||
}),
|
||||
});
|
||||
},
|
||||
});
|
||||
|
||||
const sampleDataQuery = useMemo(() => {
|
||||
|
|
|
@ -25,9 +25,9 @@ import React, { useState } from 'react';
|
|||
import { AutoForm, CenterMessage, LearnMore, Loader } from '../../../components';
|
||||
import type { InputFormat, InputSource } from '../../../druid-models';
|
||||
import {
|
||||
guessColumnTypeFromHeaderAndRows,
|
||||
guessIsArrayFromHeaderAndRows,
|
||||
INPUT_FORMAT_FIELDS,
|
||||
BATCH_INPUT_FORMAT_FIELDS,
|
||||
guessColumnTypeFromSampleResponse,
|
||||
guessIsArrayFromSampleResponse,
|
||||
inputFormatOutputsNumericStrings,
|
||||
PLACEHOLDER_TIMESTAMP_SPEC,
|
||||
possibleDruidFormatForValues,
|
||||
|
@ -41,8 +41,8 @@ import {
|
|||
filterMap,
|
||||
timeFormatToSql,
|
||||
} from '../../../utils';
|
||||
import type { SampleHeaderAndRows, SampleSpec } from '../../../utils/sampler';
|
||||
import { headerAndRowsFromSampleResponse, postToSampler } from '../../../utils/sampler';
|
||||
import type { SampleResponse, SampleSpec } from '../../../utils/sampler';
|
||||
import { getHeaderNamesFromSampleResponse, postToSampler } from '../../../utils/sampler';
|
||||
import { ParseDataTable } from '../../load-data-view/parse-data-table/parse-data-table';
|
||||
|
||||
import './input-format-step.scss';
|
||||
|
@ -76,11 +76,11 @@ export const InputFormatStep = React.memo(function InputFormatStep(props: InputF
|
|||
|
||||
const [inputFormat, setInputFormat] = useState<Partial<InputFormat>>(initInputFormat);
|
||||
const [inputFormatToSample, setInputFormatToSample] = useState<InputFormat | undefined>(
|
||||
AutoForm.isValidModel(initInputFormat, INPUT_FORMAT_FIELDS) ? initInputFormat : undefined,
|
||||
AutoForm.isValidModel(initInputFormat, BATCH_INPUT_FORMAT_FIELDS) ? initInputFormat : undefined,
|
||||
);
|
||||
const [selectTimestamp, setSelectTimestamp] = useState(true);
|
||||
|
||||
const [previewState] = useQueryManager<InputFormat, SampleHeaderAndRows>({
|
||||
const [previewState] = useQueryManager<InputFormat, SampleResponse>({
|
||||
query: inputFormatToSample,
|
||||
processQuery: async (inputFormat: InputFormat) => {
|
||||
const sampleSpec: SampleSpec = {
|
||||
|
@ -94,7 +94,9 @@ export const InputFormatStep = React.memo(function InputFormatStep(props: InputF
|
|||
dataSchema: {
|
||||
dataSource: 'sample',
|
||||
timestampSpec: PLACEHOLDER_TIMESTAMP_SPEC,
|
||||
dimensionsSpec: {},
|
||||
dimensionsSpec: {
|
||||
useSchemaDiscovery: true,
|
||||
},
|
||||
granularitySpec: {
|
||||
rollup: false,
|
||||
},
|
||||
|
@ -106,22 +108,18 @@ export const InputFormatStep = React.memo(function InputFormatStep(props: InputF
|
|||
},
|
||||
};
|
||||
|
||||
const sampleResponse = await postToSampler(sampleSpec, 'input-format-step');
|
||||
|
||||
return headerAndRowsFromSampleResponse({
|
||||
sampleResponse,
|
||||
ignoreTimeColumn: true,
|
||||
useInput: true,
|
||||
});
|
||||
return await postToSampler(sampleSpec, 'input-format-step');
|
||||
},
|
||||
});
|
||||
|
||||
const previewData = previewState.data;
|
||||
const previewSampleResponse = previewState.data;
|
||||
|
||||
let possibleTimeExpression: PossibleTimeExpression | undefined;
|
||||
if (previewData) {
|
||||
possibleTimeExpression = filterMap(previewData.header, column => {
|
||||
const values = filterMap(previewData.rows, row => row.input?.[column]);
|
||||
if (previewSampleResponse) {
|
||||
possibleTimeExpression = filterMap(
|
||||
getHeaderNamesFromSampleResponse(previewSampleResponse),
|
||||
column => {
|
||||
const values = filterMap(previewSampleResponse.data, d => d.input?.[column]);
|
||||
const possibleDruidFormat = possibleDruidFormatForValues(values);
|
||||
if (!possibleDruidFormat) return;
|
||||
|
||||
|
@ -132,27 +130,28 @@ export const InputFormatStep = React.memo(function InputFormatStep(props: InputF
|
|||
column,
|
||||
timeExpression: formatSql.fillPlaceholders([C(column)]),
|
||||
};
|
||||
})[0];
|
||||
},
|
||||
)[0];
|
||||
}
|
||||
|
||||
const inputFormatAndMore =
|
||||
previewData && AutoForm.isValidModel(inputFormat, INPUT_FORMAT_FIELDS)
|
||||
previewSampleResponse && AutoForm.isValidModel(inputFormat, BATCH_INPUT_FORMAT_FIELDS)
|
||||
? {
|
||||
inputFormat,
|
||||
signature: previewData.header.map(name =>
|
||||
signature: getHeaderNamesFromSampleResponse(previewSampleResponse, true).map(name =>
|
||||
SqlColumnDeclaration.create(
|
||||
name,
|
||||
SqlType.fromNativeType(
|
||||
guessColumnTypeFromHeaderAndRows(
|
||||
previewData,
|
||||
guessColumnTypeFromSampleResponse(
|
||||
previewSampleResponse,
|
||||
name,
|
||||
inputFormatOutputsNumericStrings(inputFormat),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
isArrays: previewData.header.map(name =>
|
||||
guessIsArrayFromHeaderAndRows(previewData, name),
|
||||
isArrays: getHeaderNamesFromSampleResponse(previewSampleResponse, true).map(name =>
|
||||
guessIsArrayFromSampleResponse(previewSampleResponse, name),
|
||||
),
|
||||
timeExpression: selectTimestamp ? possibleTimeExpression?.timeExpression : undefined,
|
||||
}
|
||||
|
@ -171,9 +170,9 @@ export const InputFormatStep = React.memo(function InputFormatStep(props: InputF
|
|||
{previewState.error && (
|
||||
<CenterMessage>{`Error: ${previewState.getErrorMessage()}`}</CenterMessage>
|
||||
)}
|
||||
{previewData && (
|
||||
{previewSampleResponse && (
|
||||
<ParseDataTable
|
||||
sampleData={previewData}
|
||||
sampleResponse={previewSampleResponse}
|
||||
columnFilter=""
|
||||
canFlatten={false}
|
||||
flattenedColumnsOnly={false}
|
||||
|
@ -191,15 +190,19 @@ export const InputFormatStep = React.memo(function InputFormatStep(props: InputF
|
|||
<LearnMore href={`${getLink('DOCS')}/ingestion/data-formats.html`} />
|
||||
</Callout>
|
||||
</FormGroup>
|
||||
<AutoForm fields={INPUT_FORMAT_FIELDS} model={inputFormat} onChange={setInputFormat} />
|
||||
<AutoForm
|
||||
fields={BATCH_INPUT_FORMAT_FIELDS}
|
||||
model={inputFormat}
|
||||
onChange={setInputFormat}
|
||||
/>
|
||||
{inputFormatToSample !== inputFormat && (
|
||||
<FormGroup className="control-buttons">
|
||||
<Button
|
||||
text="Preview changes"
|
||||
intent={Intent.PRIMARY}
|
||||
disabled={!AutoForm.isValidModel(inputFormat, INPUT_FORMAT_FIELDS)}
|
||||
disabled={!AutoForm.isValidModel(inputFormat, BATCH_INPUT_FORMAT_FIELDS)}
|
||||
onClick={() => {
|
||||
if (!AutoForm.isValidModel(inputFormat, INPUT_FORMAT_FIELDS)) return;
|
||||
if (!AutoForm.isValidModel(inputFormat, BATCH_INPUT_FORMAT_FIELDS)) return;
|
||||
setInputFormatToSample(inputFormat);
|
||||
}}
|
||||
/>
|
||||
|
|
|
@ -39,7 +39,7 @@ import {
|
|||
externalConfigToTableExpression,
|
||||
getIngestionImage,
|
||||
getIngestionTitle,
|
||||
guessInputFormat,
|
||||
guessSimpleInputFormat,
|
||||
INPUT_SOURCE_FIELDS,
|
||||
PLACEHOLDER_TIMESTAMP_SPEC,
|
||||
} from '../../../druid-models';
|
||||
|
@ -61,7 +61,7 @@ import './input-source-step.scss';
|
|||
|
||||
function resultToInputFormat(result: QueryResult): InputFormat {
|
||||
if (!result.rows.length) throw new Error('No data returned from sample query');
|
||||
return guessInputFormat(result.rows.map((r: any) => r[0]));
|
||||
return guessSimpleInputFormat(result.rows.map((r: any) => r[0]));
|
||||
}
|
||||
|
||||
const BOGUS_LIST_DELIMITER = '56616469-6de2-9da4-efb8-8f416e6e6965'; // Just a UUID to disable the list delimiter, let's hope we do not see this UUID in the data
|
||||
|
@ -129,7 +129,7 @@ export const InputSourceStep = React.memo(function InputSourceStep(props: InputS
|
|||
);
|
||||
|
||||
if (!sampleLines.length) throw new Error('No data returned from sampler');
|
||||
guessedInputFormat = guessInputFormat(sampleLines);
|
||||
guessedInputFormat = guessSimpleInputFormat(sampleLines);
|
||||
} else {
|
||||
const tableExpression = externalConfigToTableExpression({
|
||||
inputSource,
|
||||
|
|
Loading…
Reference in New Issue