docs/tutorials/tutorial-rollup.md - druid - Git at Google

 ---
 id: tutorial-rollup
 title: "Tutorial: Roll-up"
 sidebar_label: "Roll-up"
 ---

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 Apache Druid can summarize raw data at ingestion time using a process we refer to as "roll-up". Roll-up is a first-level aggregation operation over a selected set of columns that reduces the size of stored data.

 This tutorial will demonstrate the effects of roll-up on an example dataset.

 For this tutorial, we'll assume you've already downloaded Druid as described in
 the [single-machine quickstart](index.md) and have it running on your local machine.

 It will also be helpful to have finished [Tutorial: Loading a file](../tutorials/tutorial-batch.md) and [Tutorial: Querying data](../tutorials/tutorial-query.md).

 ## Example data

 For this tutorial, we'll use a small sample of network flow event data, representing packet and byte counts for traffic from a source to a destination IP address that occurred within a particular second.

 ```json
 {"timestamp":"2018-01-01T01:01:35Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":20,"bytes":9024}
 {"timestamp":"2018-01-01T01:01:51Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":255,"bytes":21133}
 {"timestamp":"2018-01-01T01:01:59Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":11,"bytes":5780}
 {"timestamp":"2018-01-01T01:02:14Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":38,"bytes":6289}
 {"timestamp":"2018-01-01T01:02:29Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":377,"bytes":359971}
 {"timestamp":"2018-01-01T01:03:29Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":49,"bytes":10204}
 {"timestamp":"2018-01-02T21:33:14Z","srcIP":"7.7.7.7", "dstIP":"8.8.8.8","packets":38,"bytes":6289}
 {"timestamp":"2018-01-02T21:33:45Z","srcIP":"7.7.7.7", "dstIP":"8.8.8.8","packets":123,"bytes":93999}
 {"timestamp":"2018-01-02T21:35:45Z","srcIP":"7.7.7.7", "dstIP":"8.8.8.8","packets":12,"bytes":2818}
 ```

 A file containing this sample input data is located at `quickstart/tutorial/rollup-data.json`.

 We'll ingest this data using the following ingestion task spec, located at `quickstart/tutorial/rollup-index.json`.

 ```json
 {
   "type" : "index_parallel",
   "spec" : {
     "dataSchema" : {
       "dataSource" : "rollup-tutorial",
       "dimensionsSpec" : {
         "dimensions" : [
           "srcIP",
           "dstIP"
         ]
       },
       "timestampSpec": {
         "column": "timestamp",
         "format": "iso"
       },
       "metricsSpec" : [
         { "type" : "count", "name" : "count" },
         { "type" : "longSum", "name" : "packets", "fieldName" : "packets" },
         { "type" : "longSum", "name" : "bytes", "fieldName" : "bytes" }
       ],
       "granularitySpec" : {
         "type" : "uniform",
         "segmentGranularity" : "week",
         "queryGranularity" : "minute",
         "intervals" : ["2018-01-01/2018-01-03"],
         "rollup" : true
       }
     },
     "ioConfig" : {
       "type" : "index_parallel",
       "inputSource" : {
         "type" : "local",
         "baseDir" : "quickstart/tutorial",
         "filter" : "rollup-data.json"
       },
       "inputFormat" : {
         "type" : "json"
       },
       "appendToExisting" : false
     },
     "tuningConfig" : {
       "type" : "index_parallel",
       "maxRowsPerSegment" : 5000000,
       "maxRowsInMemory" : 25000
     }
   }
 }
 ```

 Roll-up has been enabled by setting `"rollup" : true` in the `granularitySpec`.

 Note that we have `srcIP` and `dstIP` defined as dimensions, a longSum metric is defined for the `packets` and `bytes` columns, and the `queryGranularity` has been defined as `minute`.

 We will see how these definitions are used after we load this data.

 ## Load the example data

 From the apache-druid-{{DRUIDVERSION}} package root, run the following command:

 ```bash
 bin/post-index-task --file quickstart/tutorial/rollup-index.json --url http://localhost:8081
 ```

 After the script completes, we will query the data.

 ## Query the example data

 Let's run `bin/dsql` and issue a `select * from "rollup-tutorial";` query to see what data was ingested.

 ```bash
 $ bin/dsql
 Welcome to dsql, the command-line client for Druid SQL.
 Type "\h" for help.
 dsql> select * from "rollup-tutorial";
 ┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
 │ __time                   │ bytes  │ count │ dstIP   │ packets │ srcIP   │
 ├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
 │ 2018-01-01T01:01:00.000Z │  35937 │     3 │ 2.2.2.2 │     286 │ 1.1.1.1 │
 │ 2018-01-01T01:02:00.000Z │ 366260 │     2 │ 2.2.2.2 │     415 │ 1.1.1.1 │
 │ 2018-01-01T01:03:00.000Z │  10204 │     1 │ 2.2.2.2 │      49 │ 1.1.1.1 │
 │ 2018-01-02T21:33:00.000Z │ 100288 │     2 │ 8.8.8.8 │     161 │ 7.7.7.7 │
 │ 2018-01-02T21:35:00.000Z │   2818 │     1 │ 8.8.8.8 │      12 │ 7.7.7.7 │
 └──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
 Retrieved 5 rows in 1.18s.

 dsql>
 ```

 Let's look at the three events in the original input data that occurred during `2018-01-01T01:01`:

 ```json
 {"timestamp":"2018-01-01T01:01:35Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":20,"bytes":9024}
 {"timestamp":"2018-01-01T01:01:51Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":255,"bytes":21133}
 {"timestamp":"2018-01-01T01:01:59Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":11,"bytes":5780}
 ```

 These three rows have been "rolled up" into the following row:

 ```bash
 ┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
 │ __time                   │ bytes  │ count │ dstIP   │ packets │ srcIP   │
 ├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
 │ 2018-01-01T01:01:00.000Z │  35937 │     3 │ 2.2.2.2 │     286 │ 1.1.1.1 │
 └──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
 ```

 The input rows have been grouped by the timestamp and dimension columns `{timestamp, srcIP, dstIP}` with sum aggregations on the metric columns `packets` and `bytes`.

 Before the grouping occurs, the timestamps of the original input data are bucketed/floored by minute, due to the `"queryGranularity":"minute"` setting in the ingestion spec.

 Likewise, these two events that occurred during `2018-01-01T01:02` have been rolled up:

 ```json
 {"timestamp":"2018-01-01T01:02:14Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":38,"bytes":6289}
 {"timestamp":"2018-01-01T01:02:29Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":377,"bytes":359971}
 ```

 ```bash
 ┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
 │ __time                   │ bytes  │ count │ dstIP   │ packets │ srcIP   │
 ├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
 │ 2018-01-01T01:02:00.000Z │ 366260 │     2 │ 2.2.2.2 │     415 │ 1.1.1.1 │
 └──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
 ```

 For the last event recording traffic between 1.1.1.1 and 2.2.2.2, no roll-up took place, because this was the only event that occurred during `2018-01-01T01:03`:

 ```json
 {"timestamp":"2018-01-01T01:03:29Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":49,"bytes":10204}
 ```

 ```bash
 ┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
 │ __time                   │ bytes  │ count │ dstIP   │ packets │ srcIP   │
 ├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
 │ 2018-01-01T01:03:00.000Z │  10204 │     1 │ 2.2.2.2 │      49 │ 1.1.1.1 │
 └──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
 ```

 Note that the `count` metric shows how many rows in the original input data contributed to the final "rolled up" row.
	---
	id: tutorial-rollup
	title: "Tutorial: Roll-up"
	sidebar_label: "Roll-up"
	---

	<!--
	~ 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.
	-->


	Apache Druid can summarize raw data at ingestion time using a process we refer to as "roll-up". Roll-up is a first-level aggregation operation over a selected set of columns that reduces the size of stored data.

	This tutorial will demonstrate the effects of roll-up on an example dataset.

	For this tutorial, we'll assume you've already downloaded Druid as described in
	the [single-machine quickstart](index.md) and have it running on your local machine.

	It will also be helpful to have finished [Tutorial: Loading a file](../tutorials/tutorial-batch.md) and [Tutorial: Querying data](../tutorials/tutorial-query.md).

	## Example data

	For this tutorial, we'll use a small sample of network flow event data, representing packet and byte counts for traffic from a source to a destination IP address that occurred within a particular second.

	```json
	{"timestamp":"2018-01-01T01:01:35Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":20,"bytes":9024}
	{"timestamp":"2018-01-01T01:01:51Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":255,"bytes":21133}
	{"timestamp":"2018-01-01T01:01:59Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":11,"bytes":5780}
	{"timestamp":"2018-01-01T01:02:14Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":38,"bytes":6289}
	{"timestamp":"2018-01-01T01:02:29Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":377,"bytes":359971}
	{"timestamp":"2018-01-01T01:03:29Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":49,"bytes":10204}
	{"timestamp":"2018-01-02T21:33:14Z","srcIP":"7.7.7.7", "dstIP":"8.8.8.8","packets":38,"bytes":6289}
	{"timestamp":"2018-01-02T21:33:45Z","srcIP":"7.7.7.7", "dstIP":"8.8.8.8","packets":123,"bytes":93999}
	{"timestamp":"2018-01-02T21:35:45Z","srcIP":"7.7.7.7", "dstIP":"8.8.8.8","packets":12,"bytes":2818}
	```

	A file containing this sample input data is located at `quickstart/tutorial/rollup-data.json`.

	We'll ingest this data using the following ingestion task spec, located at `quickstart/tutorial/rollup-index.json`.

	```json
	{
	"type" : "index_parallel",
	"spec" : {
	"dataSchema" : {
	"dataSource" : "rollup-tutorial",
	"dimensionsSpec" : {
	"dimensions" : [
	"srcIP",
	"dstIP"
	]
	},
	"timestampSpec": {
	"column": "timestamp",
	"format": "iso"
	},
	"metricsSpec" : [
	{ "type" : "count", "name" : "count" },
	{ "type" : "longSum", "name" : "packets", "fieldName" : "packets" },
	{ "type" : "longSum", "name" : "bytes", "fieldName" : "bytes" }
	],
	"granularitySpec" : {
	"type" : "uniform",
	"segmentGranularity" : "week",
	"queryGranularity" : "minute",
	"intervals" : ["2018-01-01/2018-01-03"],
	"rollup" : true
	}
	},
	"ioConfig" : {
	"type" : "index_parallel",
	"inputSource" : {
	"type" : "local",
	"baseDir" : "quickstart/tutorial",
	"filter" : "rollup-data.json"
	},
	"inputFormat" : {
	"type" : "json"
	},
	"appendToExisting" : false
	},
	"tuningConfig" : {
	"type" : "index_parallel",
	"maxRowsPerSegment" : 5000000,
	"maxRowsInMemory" : 25000
	}
	}
	}
	```

	Roll-up has been enabled by setting `"rollup" : true` in the `granularitySpec`.

	Note that we have `srcIP` and `dstIP` defined as dimensions, a longSum metric is defined for the `packets` and `bytes` columns, and the `queryGranularity` has been defined as `minute`.

	We will see how these definitions are used after we load this data.

	## Load the example data

	From the apache-druid-{{DRUIDVERSION}} package root, run the following command:

	```bash
	bin/post-index-task --file quickstart/tutorial/rollup-index.json --url http://localhost:8081
	```

	After the script completes, we will query the data.

	## Query the example data

	Let's run `bin/dsql` and issue a `select * from "rollup-tutorial";` query to see what data was ingested.

	```bash
	$ bin/dsql
	Welcome to dsql, the command-line client for Druid SQL.
	Type "\h" for help.
	dsql> select * from "rollup-tutorial";
	┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
	│ __time │ bytes │ count │ dstIP │ packets │ srcIP │
	├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
	│ 2018-01-01T01:01:00.000Z │ 35937 │ 3 │ 2.2.2.2 │ 286 │ 1.1.1.1 │
	│ 2018-01-01T01:02:00.000Z │ 366260 │ 2 │ 2.2.2.2 │ 415 │ 1.1.1.1 │
	│ 2018-01-01T01:03:00.000Z │ 10204 │ 1 │ 2.2.2.2 │ 49 │ 1.1.1.1 │
	│ 2018-01-02T21:33:00.000Z │ 100288 │ 2 │ 8.8.8.8 │ 161 │ 7.7.7.7 │
	│ 2018-01-02T21:35:00.000Z │ 2818 │ 1 │ 8.8.8.8 │ 12 │ 7.7.7.7 │
	└──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
	Retrieved 5 rows in 1.18s.

	dsql>
	```

	Let's look at the three events in the original input data that occurred during `2018-01-01T01:01`:

	```json
	{"timestamp":"2018-01-01T01:01:35Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":20,"bytes":9024}
	{"timestamp":"2018-01-01T01:01:51Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":255,"bytes":21133}
	{"timestamp":"2018-01-01T01:01:59Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":11,"bytes":5780}
	```

	These three rows have been "rolled up" into the following row:

	```bash
	┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
	│ __time │ bytes │ count │ dstIP │ packets │ srcIP │
	├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
	│ 2018-01-01T01:01:00.000Z │ 35937 │ 3 │ 2.2.2.2 │ 286 │ 1.1.1.1 │
	└──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
	```

	The input rows have been grouped by the timestamp and dimension columns `{timestamp, srcIP, dstIP}` with sum aggregations on the metric columns `packets` and `bytes`.

	Before the grouping occurs, the timestamps of the original input data are bucketed/floored by minute, due to the `"queryGranularity":"minute"` setting in the ingestion spec.

	Likewise, these two events that occurred during `2018-01-01T01:02` have been rolled up:

	```json
	{"timestamp":"2018-01-01T01:02:14Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":38,"bytes":6289}
	{"timestamp":"2018-01-01T01:02:29Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":377,"bytes":359971}
	```

	```bash
	┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
	│ __time │ bytes │ count │ dstIP │ packets │ srcIP │
	├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
	│ 2018-01-01T01:02:00.000Z │ 366260 │ 2 │ 2.2.2.2 │ 415 │ 1.1.1.1 │
	└──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
	```

	For the last event recording traffic between 1.1.1.1 and 2.2.2.2, no roll-up took place, because this was the only event that occurred during `2018-01-01T01:03`:

	```json
	{"timestamp":"2018-01-01T01:03:29Z","srcIP":"1.1.1.1", "dstIP":"2.2.2.2","packets":49,"bytes":10204}
	```

	```bash
	┌──────────────────────────┬────────┬───────┬─────────┬─────────┬─────────┐
	│ __time │ bytes │ count │ dstIP │ packets │ srcIP │
	├──────────────────────────┼────────┼───────┼─────────┼─────────┼─────────┤
	│ 2018-01-01T01:03:00.000Z │ 10204 │ 1 │ 2.2.2.2 │ 49 │ 1.1.1.1 │
	└──────────────────────────┴────────┴───────┴─────────┴─────────┴─────────┘
	```

	Note that the `count` metric shows how many rows in the original input data contributed to the final "rolled up" row.