141 lines
6.7 KiB
Markdown
141 lines
6.7 KiB
Markdown
---
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layout: default
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title: Getting started
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nav_order: 5
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redirect_from:
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- /clients/data-prepper/getting-started/
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- /data-prepper/get-started/
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- /clients/data-prepper/get-started/
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---
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# Getting started with Data Prepper
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Data Prepper is an independent component, not an OpenSearch plugin, that converts data for use with OpenSearch. It's not bundled with the all-in-one OpenSearch installation packages.
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If you are migrating from Open Distro Data Prepper, visit the [Migrating from Open Distro]({{site.url}}{{site.baseurl}}/data-prepper/migrate-open-distro/) page.
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## 1. Installing Data Prepper
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There are two ways to install Data Prepper:
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1. Run the Docker image.
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2. Build from source.
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The easiest way to use Data Prepper is by running the Docker image. We suggest that you use this approach if you have [Docker](https://www.docker.com) available.
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You can pull the Docker image:
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```
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docker pull opensearchproject/data-prepper:latest
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```
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If you have special requirements that require you to build from source, or if you
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want to contribute, see the [Developer Guide](https://github.com/opensearch-project/data-prepper/blob/main/docs/developer_guide.md).
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## 2. Configuring Data Prepper
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You must configure Data Prepper with a pipeline before running it.
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You will configure two files:
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* `data-prepper-config.yaml`
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* `pipelines.yaml`
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Depending on your use case, we have a few different guides to configuring Data Prepper.
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* [Trace Analytics](https://github.com/opensearch-project/data-prepper/blob/main/docs/trace_analytics.md)
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* [Log Ingestion](https://github.com/opensearch-project/data-prepper/blob/main/docs/log_analytics.md): Learn how to set up Data Prepper for log observability.
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* [Simple Pipeline](https://github.com/opensearch-project/data-prepper/blob/main/docs/simple_pipelines.md): Learn the basics of Data Prepper pipelines with some simple configurations.
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## 3. Defining a pipeline
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Create a Data Prepper pipeline file, `pipelines.yaml`, with the following configuration:
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```yml
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simple-sample-pipeline:
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workers: 2
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delay: "5000"
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source:
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random:
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sink:
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- stdout:
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```
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## 4. Running Data Prepper
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Run the following command with your pipeline configuration YAML.
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```bash
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docker run --name data-prepper \
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-v /full/path/to/pipelines.yaml:/usr/share/data-prepper/pipelines/pipelines.yaml \
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opensearchproject/data-prepper:latest
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```
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This sample pipeline configuration above demonstrates a simple pipeline with a source (`random`) sending data to a sink (`stdout`). For more examples and details about more advanced pipeline configurations, see [Pipelines]({{site.url}}{{site.baseurl}}/clients/data-prepper/pipelines).
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After starting Data Prepper, you should see log output and some UUIDs after a few seconds:
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```yml
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2021-09-30T20:19:44,147 [main] INFO com.amazon.dataprepper.pipeline.server.DataPrepperServer - Data Prepper server running at :4900
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2021-09-30T20:19:44,681 [random-source-pool-0] INFO com.amazon.dataprepper.plugins.source.RandomStringSource - Writing to buffer
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2021-09-30T20:19:45,183 [random-source-pool-0] INFO com.amazon.dataprepper.plugins.source.RandomStringSource - Writing to buffer
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2021-09-30T20:19:45,687 [random-source-pool-0] INFO com.amazon.dataprepper.plugins.source.RandomStringSource - Writing to buffer
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2021-09-30T20:19:46,191 [random-source-pool-0] INFO com.amazon.dataprepper.plugins.source.RandomStringSource - Writing to buffer
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2021-09-30T20:19:46,694 [random-source-pool-0] INFO com.amazon.dataprepper.plugins.source.RandomStringSource - Writing to buffer
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2021-09-30T20:19:47,200 [random-source-pool-0] INFO com.amazon.dataprepper.plugins.source.RandomStringSource - Writing to buffer
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2021-09-30T20:19:49,181 [simple-test-pipeline-processor-worker-1-thread-1] INFO com.amazon.dataprepper.pipeline.ProcessWorker - simple-test-pipeline Worker: Processing 6 records from buffer
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07dc0d37-da2c-447e-a8df-64792095fb72
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5ac9b10a-1d21-4306-851a-6fb12f797010
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99040c79-e97b-4f1d-a70b-409286f2a671
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5319a842-c028-4c17-a613-3ef101bd2bdd
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e51e700e-5cab-4f6d-879a-1c3235a77d18
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b4ed2d7e-cf9c-4e9d-967c-b18e8af35c90
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```
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The remainder of this page provides examples for running Data Prepper from the Docker image. If you
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built from source, refer to the [Developer Guide](https://github.com/opensearch-project/data-prepper/blob/main/docs/developer_guide.md) for more information.
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However you configure your pipeline, you will run Data Prepper the same way. You run the Docker
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image and supply both the `pipelines.yaml` and `data-prepper-config.yaml` files.
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For Data Prepper 2.0 or later, use this command:
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```
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docker run --name data-prepper -p 4900:4900 -v ${PWD}/pipelines.yaml:/usr/share/data-prepper/pipelines/pipelines.yaml -v ${PWD}/data-prepper-config.yaml:/usr/share/data-prepper/config/data-prepper-config.yaml opensearchproject/data-prepper:latest
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```
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For Data Prepper before version 2.0, use this command:
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```
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docker run --name data-prepper -p 4900:4900 -v ${PWD}/pipelines.yaml:/usr/share/data-prepper/pipelines.yaml -v ${PWD}/data-prepper-config.yaml:/usr/share/data-prepper/data-prepper-config.yaml opensearchproject/data-prepper:1.x
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```
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Once Data Prepper is running, it will process data until it is shut down. Once you are done, shut it down with the following command:
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```
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curl -X POST http://localhost:4900/shutdown
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```
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### Additional configurations
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For Data Prepper 2.0 or later, the Log4j 2 configuration file is read from `config/log4j2.properties` in the application's home directory.
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By default, it uses `log4j2-rolling.properties` in the *shared-config* directory.
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For Data Prepper 1.5 or earlier, optionally add `"-Dlog4j.configurationFile=config/log4j2.properties"` to the command if you would
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like to pass a custom log4j2 properties file. If no properties file is provided, Data Prepper will default to the log4j2.properties file in the *shared-config* directory.
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## Next steps
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Trace Analytics is an important Data Prepper use case. If you haven't yet configured it,
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see the [Trace Analytics](https://github.com/opensearch-project/data-prepper/blob/main/docs/trace_analytics.md).
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Log Ingestion is also an important Data Prepper use case. To learn more, see the [Log Ingestion Documentation](https://github.com/opensearch-project/data-prepper/blob/main/docs/log_analytics.md).
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To learn how to run Data Prepper with a Logstash configuration, see the [Logstash Migration Guide]({{site.url}}{{site.baseurl}}/data-prepper/configure-logstash-data-prepper/).
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For information on how to monitor Data Prepper, see the [Monitoring](https://github.com/opensearch-project/data-prepper/blob/main/docs/monitoring.md) page.
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## Other examples
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We have several other Docker [examples](https://github.com/opensearch-project/data-prepper/tree/main/examples/)
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that allow you to run Data Prepper in different scenarios.
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