From 42fa5c26e1f4e09692c9752ccba6126a9ae96905 Mon Sep 17 00:00:00 2001 From: Charles Smith Date: Thu, 28 Apr 2022 16:36:54 -0700 Subject: [PATCH] remove arbitrary granularity spec from docs (#12460) * remove arbitrary granularity spec from docs * Update docs/ingestion/ingestion-spec.md Co-authored-by: Victoria Lim Co-authored-by: Victoria Lim --- docs/ingestion/ingestion-spec.md | 6 +++--- docs/tutorials/tutorial-ingestion-spec.md | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/ingestion/ingestion-spec.md b/docs/ingestion/ingestion-spec.md index 184ccb3dfbb..c87fb6141cb 100644 --- a/docs/ingestion/ingestion-spec.md +++ b/docs/ingestion/ingestion-spec.md @@ -298,11 +298,11 @@ A `granularitySpec` can have the following components: | Field | Description | Default | |-------|-------------|---------| -| type | Either `uniform` or `arbitrary`. In most cases you want to use `uniform`.| `uniform` | -| segmentGranularity | [Time chunking](../design/architecture.md#datasources-and-segments) granularity for this datasource. Multiple segments can be created per time chunk. For example, when set to `day`, the events of the same day fall into the same time chunk which can be optionally further partitioned into multiple segments based on other configurations and input size. Any [granularity](../querying/granularities.md) can be provided here. Note that all segments in the same time chunk should have the same segment granularity.

Ignored if `type` is set to `arbitrary`.| `day` | +| type |`uniform`| `uniform` | +| segmentGranularity | [Time chunking](../design/architecture.md#datasources-and-segments) granularity for this datasource. Multiple segments can be created per time chunk. For example, when set to `day`, the events of the same day fall into the same time chunk which can be optionally further partitioned into multiple segments based on other configurations and input size. Any [granularity](../querying/granularities.md) can be provided here. Note that all segments in the same time chunk should have the same segment granularity.| `day` | | queryGranularity | The resolution of timestamp storage within each segment. This must be equal to, or finer, than `segmentGranularity`. This will be the finest granularity that you can query at and still receive sensible results, but note that you can still query at anything coarser than this granularity. E.g., a value of `minute` will mean that records will be stored at minutely granularity, and can be sensibly queried at any multiple of minutes (including minutely, 5-minutely, hourly, etc).

Any [granularity](../querying/granularities.md) can be provided here. Use `none` to store timestamps as-is, without any truncation. Note that `rollup` will be applied if it is set even when the `queryGranularity` is set to `none`. | `none` | | rollup | Whether to use ingestion-time [rollup](./rollup.md) or not. Note that rollup is still effective even when `queryGranularity` is set to `none`. Your data will be rolled up if they have the exactly same timestamp. | `true` | -| intervals | A list of intervals defining time chunks for segments. Specify interval values using ISO8601 format. For example, `["2021-12-06T21:27:10+00:00/2021-12-07T00:00:00+00:00"]`. If you omit the time, the time defaults to "00:00:00".

If `type` is set to `uniform`, Druid breaks the list up and rounds-off the list values based on the `segmentGranularity`. If `type` is set to `arbitrary`, Druid uses the list as-is.

If `null` or not provided, batch ingestion tasks generally determine which time chunks to output based on the timestamps found in the input data.

If specified, batch ingestion tasks may be able to skip a determining-partitions phase, which can result in faster ingestion. Batch ingestion tasks may also be able to request all their locks up-front instead of one by one. Batch ingestion tasks throw away any records with timestamps outside of the specified intervals.

Ignored for any form of streaming ingestion. | `null` | +| intervals | A list of intervals defining time chunks for segments. Specify interval values using ISO8601 format. For example, `["2021-12-06T21:27:10+00:00/2021-12-07T00:00:00+00:00"]`. If you omit the time, the time defaults to "00:00:00".

Druid breaks the list up and rounds off the list values based on the `segmentGranularity`.

If `null` or not provided, batch ingestion tasks generally determine which time chunks to output based on the timestamps found in the input data.

If specified, batch ingestion tasks may be able to skip a determining-partitions phase, which can result in faster ingestion. Batch ingestion tasks may also be able to request all their locks up-front instead of one by one. Batch ingestion tasks throw away any records with timestamps outside of the specified intervals.

Ignored for any form of streaming ingestion. | `null` | ### `transformSpec` diff --git a/docs/tutorials/tutorial-ingestion-spec.md b/docs/tutorials/tutorial-ingestion-spec.md index 821c376f637..13a0b8700df 100644 --- a/docs/tutorials/tutorial-ingestion-spec.md +++ b/docs/tutorials/tutorial-ingestion-spec.md @@ -251,7 +251,7 @@ If we were not using rollup, all columns would be specified in the `dimensionsSp At this point, we are done defining the `parser` and `metricsSpec` within the `dataSchema` and we are almost done writing the ingestion spec. There are some additional properties we need to set in the `granularitySpec`: -* Type of granularitySpec: `uniform` and `arbitrary` are the two supported types. For this tutorial, we will use a `uniform` granularity spec, where all segments have uniform interval sizes (for example, all segments cover an hour's worth of data). +* Type of granularitySpec: the `uniform` granularity spec defines segments with uniform interval sizes. For example, all segments cover an hour's worth of data. * The segment granularity: what size of time interval should a single segment contain data for? e.g., `DAY`, `WEEK` * The bucketing granularity of the timestamps in the time column (referred to as `queryGranularity`)