docs/tutorials/tutorial-append-data.md

id: tutorial-append-data title: Append data sidebar_label: Append data description: Learn how to append data to a datasource without changing the existing data in Apache Druid.

This tutorial shows you how to use the Apache Druid SQL INSERT function to append data to a datasource without changing the existing data. The examples in the tutorial use the multi-stage query (MSQ) task engine to executes SQL statements.

Prerequisites

Before you follow the steps in this tutorial, download Druid as described in Quickstart (local) 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 tutorial first.

Load sample data

Load a sample dataset using INSERT and EXTERN functions. The EXTERN function lets you read external data or write to an external location.

In the Druid web console, go to the Query view and run the following query:

INSERT INTO "append_tutorial"
SELECT
  TIME_PARSE("timestamp") AS "__time",
  "animal",
  "number"
FROM TABLE(
  EXTERN(
    '{"type":"inline","data":"{\"timestamp\":\"2024-01-01T07:01:35Z\",\"animal\":\"octopus\", \"number\":115}\n{\"timestamp\":\"2024-01-01T05:01:35Z\",\"animal\":\"mongoose\", \"number\":737}\n{\"timestamp\":\"2024-01-01T06:01:35Z\",\"animal\":\"snake\", \"number\":1234}\n{\"timestamp\":\"2024-01-01T01:01:35Z\",\"animal\":\"lion\", \"number\":300}\n{\"timestamp\":\"2024-01-02T07:01:35Z\",\"animal\":\"seahorse\", \"number\":115}\n{\"timestamp\":\"2024-01-02T05:01:35Z\",\"animal\":\"skunk\", \"number\":737}\n{\"timestamp\":\"2024-01-02T06:01:35Z\",\"animal\":\"iguana\", \"number\":1234}\n{\"timestamp\":\"2024-01-02T01:01:35Z\",\"animal\":\"opossum\", \"number\":300}"}',
      '{"type":"json"}'
    )
  ) EXTEND ("timestamp" VARCHAR, "animal" VARCHAR, "number" BIGINT)
PARTITIONED BY DAY

The resulting append_tutorial datasource contains records for eight animals over two days. To view the results, open a new tab and run the following query:

SELECT * FROM "append_tutorial"

`__time`	`animal`	`number`
`2024-01-01T01:01:35.000Z`	`lion`	300
`2024-01-01T05:01:35.000Z`	`mongoose`	737
`2024-01-01T06:01:35.000Z`	`snake`	1234
`2024-01-01T07:01:35.000Z`	`octopus`	115
`2024-01-02T01:01:35.000Z`	`opossum`	300
`2024-01-02T05:01:35.000Z`	`skunk`	737
`2024-01-02T06:01:35.000Z`	`iguana`	1234
`2024-01-02T07:01:35.000Z`	`seahorse`	115

Append data

You can use the INSERT function to append data to the datasource without changing the existing data. In a new tab, run the following query to ingest and append data to the append_tutorial datasource:

INSERT INTO "append_tutorial"
SELECT
  TIME_PARSE("timestamp") AS "__time",
  "animal",
  "number"
FROM TABLE(
  EXTERN(
    '{"type":"inline","data":"{\"timestamp\":\"2024-01-03T01:09:35Z\",\"animal\":\"zebra\", \"number\":233}\n{\"timestamp\":\"2024-01-04T07:01:35Z\",\"animal\":\"bear\", \"number\":577}\n{\"timestamp\":\"2024-01-04T05:01:35Z\",\"animal\":\"falcon\", \"number\":848}\n{\"timestamp\":\"2024-01-04T06:01:35Z\",\"animal\":\"giraffe\", \"number\":113}\n{\"timestamp\":\"2024-01-04T01:01:35Z\",\"animal\":\"rhino\", \"number\":473}"}',
    '{"type":"json"}'
    )
  ) EXTEND ("timestamp" VARCHAR, "animal" VARCHAR, "number" BIGINT)
PARTITIONED BY DAY

Druid adds rows for the subsequent days after seahorse. When the task completes, open a new tab and run the following query to view the results:

SELECT * FROM "append_tutorial"

`__time`	`animal`	`number`
`2024-01-01T01:01:35.000Z`	`lion`	300
`2024-01-01T05:01:35.000Z`	`mongoose`	737
`2024-01-01T06:01:35.000Z`	`snake`	1234
`2024-01-01T07:01:35.000Z`	`octopus`	115
`2024-01-02T01:01:35.000Z`	`opossum`	300
`2024-01-02T05:01:35.000Z`	`skunk`	737
`2024-01-02T06:01:35.000Z`	`iguana`	1234
`2024-01-02T07:01:35.000Z`	`seahorse`	115
`2024-01-03T01:09:35.000Z`	`zebra`	233
`2024-01-04T01:01:35.000Z`	`rhino`	473
`2024-01-04T05:01:35.000Z`	`falcon`	848
`2024-01-04T06:01:35.000Z`	`giraffe`	113
`2024-01-04T07:01:35.000Z`	`bear`	577

Learn more

See the following topics for more information:

SQL-based ingestion reference for a reference on MSQ architecture.
SQL-based ingestion query examples for example queries using the MSQ task engine.