edgar2020 commented on code in PR #16845: URL: https://github.com/apache/druid/pull/16845#discussion_r1719144131
########## docs/tutorials/tutorial-transform.md: ########## @@ -0,0 +1,101 @@ +--- +id: tutorial-transform +title: Transform input data +sidebar_label: Transform input data +--- + +<!-- + ~ 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. + --> + + +This tutorial demonstrates how to transform input data during ingestion. + +## Prerequisite + +Before proceeding, download Druid as described in [Quickstart (local)](index.md) and have it running on your local machine. You don't need to load any data into the Druid cluster. + +You should be familiar with data querying in Druid. If you haven't already, go through the [Query data](../tutorials/tutorial-query.md) tutorial first. + +## Sample data + +For this tutorial, you use the following sample data: + +```json +{"timestamp":"2018-01-01T07:01:35Z", "animal":"octopus", "location":1, "number":100} +{"timestamp":"2018-01-01T05:01:35Z", "animal":"mongoose", "location":2,"number":200} +{"timestamp":"2018-01-01T06:01:35Z", "animal":"snake", "location":3, "number":300} +{"timestamp":"2018-01-01T01:01:35Z", "animal":"lion", "location":4, "number":300} +``` + +## Transform data during ingestion + +Load the sample dataset using the [`INSERT INTO`](../multi-stage-query/reference.md/#insert) statement and the [`EXTERN`](../multi-stage-query/reference.md/#extern-function) function to ingest the data inline. In the [Druid web console](../operations/web-console.md), go to the **Query** view and run the following query: + +```sql +INSERT INTO "transform_tutorial" +WITH "ext" AS ( + SELECT * + FROM TABLE(EXTERN('{"type":"inline","data":"{\"timestamp\":\"2018-01-01T07:01:35Z\",\"animal\":\"octopus\", \"location\":1, \"number\":100}\n{\"timestamp\":\"2018-01-01T05:01:35Z\",\"animal\":\"mongoose\", \"location\":2,\"number\":200}\n{\"timestamp\":\"2018-01-01T06:01:35Z\",\"animal\":\"snake\", \"location\":3, \"number\":300}\n{\"timestamp\":\"2018-01-01T01:01:35Z\",\"animal\":\"lion\", \"location\":4, \"number\":300}"}', '{"type":"json"}')) EXTEND ("timestamp" VARCHAR, "animal" VARCHAR, "location" BIGINT, "number" BIGINT) +) +SELECT + TIME_PARSE("timestamp") AS "__time", + TEXTCAT('super-', "animal") AS "animal", + "location", + "number", + "number" * 3 AS "triple-number" +FROM "ext" +WHERE (TEXTCAT('super-', "animal") = 'super-mongoose' OR "location" = 3 OR "number" = 100) +PARTITIONED BY DAY +``` + +In the `SELECT` clause, you specify the following transformations: +* `animal`: prepends "super-" to the values in the `animal` column using the [`TEXTCAT`](../querying/sql-functions.md/#textcat) function. Note that it only ingests the transformed data. +* `triple-number`: multiplies the `number` column by three and stores the results in a column named `triple-number`. Note that the query ingests both the original and the transformed data. + +Additionally, the `WHERE` clause applies the following three OR operators so that the query only ingests the rows where at least one of the following conditions is `true`: + +* `TEXTCAT('super-', "animal")` matches "super-mongoose" +* `location` matches 3 +* `number` matches 100 + +## Query the transformed data + +In the web console, open a new tab in the **Query** view. Run the following query to view the ingested data: + +```sql +SELECT * FROM "transform_tutorial" +``` + +Returns the following: + +| `__time` | `animal` | `location` | `number` | `triple-number` | +| -- | -- | -- | -- | -- | +| `2018-01-01T05:01:35.000Z` | `super-mongoose` | `2` | `200` | `600` | +| `2018-01-01T06:01:35.000Z` | `super-snake` | `3` | `300` | `900` | +| `2018-01-01T07:01:35.000Z` | `super-octopus` | `1` | `100` | `300` | + +Once a row is accepted by the filter, the ingestion job applies the transformations. In this example, the filter selects the first three rows because each row meets at least one of the necessary OR conditions. Note that for the three rows selected, the ingestion job ingests the transformed `animal` column, the `location` column, and both the original `number` and the transformed `triple-number` column. The "lion" row is not accepted by the filter, so it is not ingested or transformed. Review Comment: I moved the paragraph to the end of "Transform data during ingestion" and added one sentance to the end of the "Query the transformed data" section to replicate the original concluding paragraph -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
