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* Various documentation updates.
1) Split out "data management" from "ingestion". Break it into thematic pages.
2) Move "SQL-based ingestion" into the Ingestion category. Adjust content so
all conceptual content is in concepts.md and all syntax content is in reference.md.
Shorten the known issues page to the most interesting ones.
3) Add SQL-based ingestion to the ingestion method comparison page. Remove the
index task, since index_parallel is just as good when maxNumConcurrentSubTasks: 1.
4) Rename various mentions of "Druid console" to "web console".
5) Add additional information to ingestion/partitioning.md.
6) Remove a mention of Tranquility.
7) Remove a note about upgrading to Druid 0.10.1.
8) Remove no-longer-relevant task types from ingestion/tasks.md.
9) Move ingestion/native-batch-firehose.md to the hidden section. It was previously deprecated.
10) Move ingestion/native-batch-simple-task.md to the hidden section. It is still linked in some
places, but it isn't very useful compared to index_parallel, so it shouldn't take up space
in the sidebar.
11) Make all br tags self-closing.
12) Certain other cosmetic changes.
13) Update to node-sass 7.
* make travis use node12 for docs
Co-authored-by: Vadim Ogievetsky <vadim@ogievetsky.com>
148 lines
6.9 KiB
Markdown
148 lines
6.9 KiB
Markdown
---
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id: tutorial-msq-extern
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title: "Tutorial: Load files with SQL-based ingestion"
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sidebar_label: "Load files using SQL 🆕"
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description: How to generate a query that references externally hosted data
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---
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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,
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~ software distributed under the License is distributed on an
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~ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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~ KIND, either express or implied. See the License for the
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~ specific language governing permissions and limitations
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~ under the License.
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-->
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> This page describes SQL-based batch ingestion using the [`druid-multi-stage-query`](../multi-stage-query/index.md)
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> extension, new in Druid 24.0. Refer to the [ingestion methods](../ingestion/index.md#batch) table to determine which
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> ingestion method is right for you.
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This tutorial demonstrates how to generate a query that references externally hosted data using the **Connect external data** wizard.
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The following example uses EXTERN to query a JSON file located at https://druid.apache.org/data/wikipedia.json.gz.
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Although you can manually create a query in the UI, you can use Druid to generate a base query for you that you can modify to meet your requirements.
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To generate a query from external data, do the following:
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1. In the **Query** view of the web console, click **Connect external data**.
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2. On the **Select input type** screen, choose **HTTP(s)** and enter the following value in the **URIs** field: `https://druid.apache.org/data/wikipedia.json.gz`. Leave the HTTP auth username and password blank.
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3. Click **Connect data**.
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4. On the **Parse** screen, you can perform additional actions before you load the data into Druid:
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- Expand a row to see what data it corresponds to from the source.
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- Customize how Druid handles the data by selecting the **Input format** and its related options, such as adding **JSON parser features** for JSON files.
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5. When you're ready, click **Done**. You're returned to the **Query** view where you can see the starter query that will insert the data from the external source into a table named `wikipedia`.
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<details><summary>Show the query</summary>
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```sql
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REPLACE INTO "wikipedia" OVERWRITE ALL
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WITH ext AS (SELECT *
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FROM TABLE(
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EXTERN(
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'{"type":"http","uris":["https://druid.apache.org/data/wikipedia.json.gz"]}',
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'{"type":"json"}',
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'[{"name":"isRobot","type":"string"},{"name":"channel","type":"string"},{"name":"timestamp","type":"string"},{"name":"flags","type":"string"},{"name":"isUnpatrolled","type":"string"},{"name":"page","type":"string"},{"name":"diffUrl","type":"string"},{"name":"added","type":"long"},{"name":"comment","type":"string"},{"name":"commentLength","type":"long"},{"name":"isNew","type":"string"},{"name":"isMinor","type":"string"},{"name":"delta","type":"long"},{"name":"isAnonymous","type":"string"},{"name":"user","type":"string"},{"name":"deltaBucket","type":"long"},{"name":"deleted","type":"long"},{"name":"namespace","type":"string"},{"name":"cityName","type":"string"},{"name":"countryName","type":"string"},{"name":"regionIsoCode","type":"string"},{"name":"metroCode","type":"long"},{"name":"countryIsoCode","type":"string"},{"name":"regionName","type":"string"}]'
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)
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))
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SELECT
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TIME_PARSE("timestamp") AS __time,
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isRobot,
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channel,
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flags,
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isUnpatrolled,
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page,
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diffUrl,
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added,
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comment,
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commentLength,
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isNew,
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isMinor,
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delta,
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isAnonymous,
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user,
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deltaBucket,
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deleted,
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namespace,
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cityName,
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countryName,
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regionIsoCode,
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metroCode,
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countryIsoCode,
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regionName
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FROM ext
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PARTITIONED BY DAY
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```
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</details>
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6. Review and modify the query to meet your needs. For example, you can rename the table or change segment granularity. To partition by something other than ALL, include `TIME_PARSE("timestamp") AS __time` in your SELECT statement.
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For example, to specify day-based segment granularity, change the partitioning to `PARTITIONED BY DAY`:
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```sql
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INSERT INTO ...
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SELECT
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TIME_PARSE("timestamp") AS __time,
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...
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...
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PARTITIONED BY DAY
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```
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1. Optionally, select **Preview** to review the data before you ingest it. A preview runs the query without the REPLACE INTO clause and with an added LIMIT.
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You can see the general shape of the data before you commit to inserting it.
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The LIMITs make the query run faster but can cause incomplete results.
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2. Click **Run** to launch your query. The query returns information including its duration and the number of rows inserted into the table.
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## Query the data
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You can query the `wikipedia` table after the ingestion completes.
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For example, you can analyze the data in the table to produce a list of top channels:
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```sql
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SELECT
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channel,
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COUNT(*)
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FROM "wikipedia"
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GROUP BY channel
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ORDER BY COUNT(*) DESC
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```
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With the EXTERN function, you could run the same query on the external data directly without ingesting it first:
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<details><summary>Show the query</summary>
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```sql
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SELECT
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channel,
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COUNT(*)
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FROM TABLE(
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EXTERN(
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'{"type": "http", "uris": ["https://druid.apache.org/data/wikipedia.json.gz"]}',
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'{"type": "json"}',
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'[{"name": "added", "type": "long"}, {"name": "channel", "type": "string"}, {"name": "cityName", "type": "string"}, {"name": "comment", "type": "string"}, {"name": "commentLength", "type": "long"}, {"name": "countryIsoCode", "type": "string"}, {"name": "countryName", "type": "string"}, {"name": "deleted", "type": "long"}, {"name": "delta", "type": "long"}, {"name": "deltaBucket", "type": "string"}, {"name": "diffUrl", "type": "string"}, {"name": "flags", "type": "string"}, {"name": "isAnonymous", "type": "string"}, {"name": "isMinor", "type": "string"}, {"name": "isNew", "type": "string"}, {"name": "isRobot", "type": "string"}, {"name": "isUnpatrolled", "type": "string"}, {"name": "metroCode", "type": "string"}, {"name": "namespace", "type": "string"}, {"name": "page", "type": "string"}, {"name": "regionIsoCode", "type": "string"}, {"name": "regionName", "type": "string"}, {"name": "timestamp", "type": "string"}, {"name": "user", "type": "string"}]'
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)
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)
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GROUP BY channel
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ORDER BY COUNT(*) DESC
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```
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</details>
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## Further reading
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See the following topics to learn more:
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* [SQL-based ingestion overview](../multi-stage-query/index.md) to further explore SQL-based ingestion.
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* [SQL-based ingestion reference](../multi-stage-query/reference.md) for reference on context parameters, functions, and error codes.
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