mirror of https://github.com/apache/druid.git
265 lines
13 KiB
Markdown
265 lines
13 KiB
Markdown
---
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id: index
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title: "Quickstart"
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---
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<!--
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This quickstart gets you started with Apache Druid and introduces you to some of its basic features.
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Following these steps, you will install Druid and load sample
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data using its native batch ingestion feature.
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Before starting, you may want to read the [general Druid overview](../design/index.md) and
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[ingestion overview](../ingestion/index.md), as the tutorials refer to concepts discussed on those pages.
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## Requirements
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You can follow these steps on a relatively small machine, such as a laptop with around 4 CPU and 16 GB of RAM.
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Druid comes with several startup configuration profiles for a range of machine sizes.
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The `micro-quickstart`configuration profile shown here is suitable for evaluating Druid. If you want to
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try out Druid's performance or scaling capabilities, you'll need a larger machine and configuration profile.
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The configuration profiles included with Druid range from the even smaller _Nano-Quickstart_ configuration (1 CPU, 4GB RAM)
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to the _X-Large_ configuration (64 CPU, 512GB RAM). For more information, see
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[Single server deployment](../operations/single-server.md). Alternatively, see [Clustered deployment](./cluster.md) for
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information on deploying Druid services across clustered machines.
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The software requirements for the installation machine are:
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* Linux, Mac OS X, or other Unix-like OS (Windows is not supported)
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* Java 8, Update 92 or later (8u92+)
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> Druid officially supports Java 8 only. Support for later major versions of Java is currently in experimental status.
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> Druid relies on the environment variables `JAVA_HOME` or `DRUID_JAVA_HOME` to find Java on the machine. You can set
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`DRUID_JAVA_HOME` if there is more than one instance of Java. To verify Java requirements for your environment, run the
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`bin/verify-java` script.
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## Step 1. Install Druid
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After confirming the [requirements](#requirements), follow these steps:
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1. Download
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the [{{DRUIDVERSION}} release](https://www.apache.org/dyn/closer.cgi?path=/druid/{{DRUIDVERSION}}/apache-druid-{{DRUIDVERSION}}-bin.tar.gz).
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2. In your terminal, extract Druid and change directories to the distribution directory:
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```bash
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tar -xzf apache-druid-{{DRUIDVERSION}}-bin.tar.gz
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cd apache-druid-{{DRUIDVERSION}}
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```
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In the directory, you'll find `LICENSE` and `NOTICE` files and subdirectories for executable files, configuration files, sample data and more.
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## Step 2: Start up Druid services
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Start up Druid services using the `micro-quickstart` single-machine configuration.
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From the apache-druid-{{DRUIDVERSION}} package root, run the following command:
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```bash
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./bin/start-micro-quickstart
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```
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This brings up instances of ZooKeeper and the Druid services:
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```bash
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$ ./bin/start-micro-quickstart
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[Fri May 3 11:40:50 2019] Running command[zk], logging to[/apache-druid-{{DRUIDVERSION}}/var/sv/zk.log]: bin/run-zk conf
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[Fri May 3 11:40:50 2019] Running command[coordinator-overlord], logging to[/apache-druid-{{DRUIDVERSION}}/var/sv/coordinator-overlord.log]: bin/run-druid coordinator-overlord conf/druid/single-server/micro-quickstart
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[Fri May 3 11:40:50 2019] Running command[broker], logging to[/apache-druid-{{DRUIDVERSION}}/var/sv/broker.log]: bin/run-druid broker conf/druid/single-server/micro-quickstart
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[Fri May 3 11:40:50 2019] Running command[router], logging to[/apache-druid-{{DRUIDVERSION}}/var/sv/router.log]: bin/run-druid router conf/druid/single-server/micro-quickstart
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[Fri May 3 11:40:50 2019] Running command[historical], logging to[/apache-druid-{{DRUIDVERSION}}/var/sv/historical.log]: bin/run-druid historical conf/druid/single-server/micro-quickstart
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[Fri May 3 11:40:50 2019] Running command[middleManager], logging to[/apache-druid-{{DRUIDVERSION}}/var/sv/middleManager.log]: bin/run-druid middleManager conf/druid/single-server/micro-quickstart
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```
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All persistent state, such as the cluster metadata store and segments for the services, are kept in the `var` directory under
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the Druid root directory, apache-druid-{{DRUIDVERSION}}. Each service writes to a log file under `var/sv`, as noted in the startup script output above.
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At any time, you can revert Druid to its original, post-installation state by deleting the entire `var` directory. You may
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want to do this, for example, between Druid tutorials or after experimentation, to start with a fresh instance.
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To stop Druid at any time, use CTRL-C in the terminal. This exits the `bin/start-micro-quickstart` script and
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terminates all Druid processes.
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## Step 3. Open the Druid console
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After the Druid services finish startup, open the [Druid console](../operations/druid-console.md) at [http://localhost:8888](http://localhost:8888).
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It may take a few seconds for all Druid services to finish starting, including the [Druid router](../design/router.md), which serves the console. If you attempt to open the Druid console before startup is complete, you may see errors in the browser. Wait a few moments and try again.
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## Step 4. Load data
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Ingestion specs define the schema of the data Druid reads and stores. You can write ingestion specs by hand or using the _data loader_,
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as we'll do here to perform batch file loading with Druid's native batch ingestion.
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The Druid distribution bundles sample data we can use. The sample data located in `quickstart/tutorial/wikiticker-2015-09-12-sampled.json.gz`
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in the Druid root directory represents Wikipedia page edits for a given day.
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1. Click **Load data** from the Druid console header ().
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2. Select the **Local disk** tile and then click **Connect data**.
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3. Enter the following values:
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- **Base directory**: `quickstart/tutorial/`
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- **File filter**: `wikiticker-2015-09-12-sampled.json.gz`
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Entering the base directory and [wildcard file filter](https://commons.apache.org/proper/commons-io/apidocs/org/apache/commons/io/filefilter/WildcardFileFilter.html) separately, as afforded by the UI, allows you to specify multiple files for ingestion at once.
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4. Click **Apply**.
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The data loader displays the raw data, giving you a chance to verify that the data
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appears as expected.
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Notice that your position in the sequence of steps to load data, **Connect** in our case, appears at the top of the console, as shown below.
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You can click other steps to move forward or backward in the sequence at any time.
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5. Click **Next: Parse data**.
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The data loader tries to determine the parser appropriate for the data format automatically. In this case
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it identifies the data format as `json`, as shown in the **Input format** field at the bottom right.
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Feel free to select other **Input format** options to get a sense of their configuration settings
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and how Druid parses other types of data.
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6. With the JSON parser selected, click **Next: Parse time**. The **Parse time** settings are where you view and adjust the
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primary timestamp column for the data.
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Druid requires data to have a primary timestamp column (internally stored in a column called `__time`).
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If you do not have a timestamp in your data, select `Constant value`. In our example, the data loader
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determines that the `time` column is the only candidate that can be used as the primary time column.
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7. Click **Next: Transform**, **Next: Filter**, and then **Next: Configure schema**, skipping a few steps.
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You do not need to adjust transformation or filtering settings, as applying ingestion time transforms and
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filters are out of scope for this tutorial.
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8. The Configure schema settings are where you configure what [dimensions](../ingestion/index.md#dimensions)
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and [metrics](../ingestion/index.md#metrics) are ingested. The outcome of this configuration represents exactly how the
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data will appear in Druid after ingestion.
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Since our dataset is very small, you can turn off [rollup](../ingestion/index.md#rollup)
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by unsetting the **Rollup** switch and confirming the change when prompted.
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10. Click **Next: Partition** to configure how the data will be split into segments. In this case, choose `DAY` as
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the **Segment granularity**.
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Since this is a small dataset, we can have just a single segment, which is what selecting `DAY` as the
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segment granularity gives us.
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11. Click **Next: Tune** and **Next: Publish**.
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12. The Publish settings are where you specify the datasource name in Druid. Let's change the default name from
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`wikiticker-2015-09-12-sampled` to `wikipedia`.
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13. Click **Next: Edit spec** to review the ingestion spec we've constructed with the data loader.
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Feel free to go back and change settings from previous steps to see how doing so updates the spec.
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Similarly, you can edit the spec directly and see it reflected in the previous steps.
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> For other ways to load ingestion specs in Druid, see [Tutorial: Loading a file](./tutorial-batch.md).
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14. Once you are satisfied with the spec, click **Submit**.
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The new task for our wikipedia datasource now appears in the Ingestion view.
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The task may take a minute or two to complete. When done, the task status should be "SUCCESS", with
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the duration of the task indicated. Note that the view is set to automatically
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refresh, so you do not need to refresh the browser to see the status change.
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A successful task means that one or more segments have been built and are now picked up by our data servers.
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## Step 5. Query the data
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You can now see the data as a datasource in the console and try out a query, as follows:
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1. Click **Datasources** from the console header.
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If the wikipedia datasource doesn't appear, wait a few moments for the segment to finish loading. A datasource is
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queryable once it is shown to be "Fully available" in the **Availability** column.
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2. When the datasource is available, open the Actions menu () for that
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datasource and choose **Query with SQL**.
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> Notice the other actions you can perform for a datasource, including configuring retention rules, compaction, and more.
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3. Run the prepopulated query, `SELECT * FROM "wikipedia"` to see the results.
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Congratulations! You've gone from downloading Druid to querying data in just one quickstart. See the following
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section for what to do next.
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## Next steps
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After finishing the quickstart, check out the [query tutorial](../tutorials/tutorial-query.md) to further explore
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Query features in the Druid console.
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Alternatively, learn about other ways to ingest data in one of these tutorials:
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- [Loading stream data from Apache Kafka](./tutorial-kafka.md) – How to load streaming data from a Kafka topic.
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- [Loading a file using Apache Hadoop](./tutorial-batch-hadoop.md) – How to perform a batch file load, using a remote Hadoop cluster.
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- [Writing your own ingestion spec](./tutorial-ingestion-spec.md) – How to write a new ingestion spec and use it to load data.
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Remember that after stopping Druid services, you can start clean next time by deleting the `var` directory from the Druid root directory and
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running the `bin/start-micro-quickstart` script again. You will likely want to do this before taking other data ingestion tutorials,
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since in them you will create the same wikipedia datasource.
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