mirror of https://github.com/apache/druid.git
167 lines
7.8 KiB
Markdown
167 lines
7.8 KiB
Markdown
---
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id: hdfs
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title: "HDFS"
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---
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<!--
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~ Licensed to the Apache Software Foundation (ASF) under one
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To use this Apache Druid extension, [include](../../configuration/extensions.md#loading-extensions) `druid-hdfs-storage` in the extensions load list and run druid processes with `GOOGLE_APPLICATION_CREDENTIALS=/path/to/service_account_keyfile` in the environment.
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## Deep Storage
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### Configuration for HDFS
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|Property|Possible Values|Description|Default|
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|--------|---------------|-----------|-------|
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|`druid.storage.type`|hdfs||Must be set.|
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|`druid.storage.storageDirectory`||Directory for storing segments.|Must be set.|
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|`druid.hadoop.security.kerberos.principal`|`druid@EXAMPLE.COM`| Principal user name |empty|
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|`druid.hadoop.security.kerberos.keytab`|`/etc/security/keytabs/druid.headlessUser.keytab`|Path to keytab file|empty|
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Besides the above settings, you also need to include all Hadoop configuration files (such as `core-site.xml`, `hdfs-site.xml`)
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in the Druid classpath. One way to do this is copying all those files under `${DRUID_HOME}/conf/_common`.
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If you are using the Hadoop ingestion, set your output directory to be a location on Hadoop and it will work.
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If you want to eagerly authenticate against a secured hadoop/hdfs cluster you must set `druid.hadoop.security.kerberos.principal` and `druid.hadoop.security.kerberos.keytab`, this is an alternative to the cron job method that runs `kinit` command periodically.
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### Configuration for Cloud Storage
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You can also use the Amazon S3 or the Google Cloud Storage as the deep storage via HDFS.
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#### Configuration for Amazon S3
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To use the Amazon S3 as the deep storage, you need to configure `druid.storage.storageDirectory` properly.
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|Property|Possible Values|Description|Default|
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|--------|---------------|-----------|-------|
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|`druid.storage.type`|hdfs| |Must be set.|
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|`druid.storage.storageDirectory`|s3a://bucket/example/directory or s3n://bucket/example/directory|Path to the deep storage|Must be set.|
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You also need to include the [Hadoop AWS module](https://hadoop.apache.org/docs/stable/hadoop-aws/tools/hadoop-aws/), especially the `hadoop-aws.jar` in the Druid classpath.
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Run the below command to install the `hadoop-aws.jar` file under `${DRUID_HOME}/extensions/druid-hdfs-storage` in all nodes.
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```bash
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${DRUID_HOME}/bin/run-java -classpath "${DRUID_HOME}/lib/*" org.apache.druid.cli.Main tools pull-deps -h "org.apache.hadoop:hadoop-aws:${HADOOP_VERSION}";
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cp ${DRUID_HOME}/hadoop-dependencies/hadoop-aws/${HADOOP_VERSION}/hadoop-aws-${HADOOP_VERSION}.jar ${DRUID_HOME}/extensions/druid-hdfs-storage/
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```
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Finally, you need to add the below properties in the `core-site.xml`.
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For more configurations, see the [Hadoop AWS module](https://hadoop.apache.org/docs/stable/hadoop-aws/tools/hadoop-aws/).
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```xml
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<property>
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<name>fs.s3a.impl</name>
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<value>org.apache.hadoop.fs.s3a.S3AFileSystem</value>
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<description>The implementation class of the S3A Filesystem</description>
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</property>
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<property>
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<name>fs.AbstractFileSystem.s3a.impl</name>
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<value>org.apache.hadoop.fs.s3a.S3A</value>
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<description>The implementation class of the S3A AbstractFileSystem.</description>
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</property>
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<property>
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<name>fs.s3a.access.key</name>
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<description>AWS access key ID. Omit for IAM role-based or provider-based authentication.</description>
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<value>your access key</value>
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</property>
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<property>
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<name>fs.s3a.secret.key</name>
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<description>AWS secret key. Omit for IAM role-based or provider-based authentication.</description>
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<value>your secret key</value>
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</property>
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```
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#### Configuration for Google Cloud Storage
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To use the Google Cloud Storage as the deep storage, you need to configure `druid.storage.storageDirectory` properly.
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|Property|Possible Values|Description|Default|
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|--------|---------------|-----------|-------|
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|`druid.storage.type`|hdfs||Must be set.|
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|`druid.storage.storageDirectory`|gs://bucket/example/directory|Path to the deep storage|Must be set.|
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All services that need to access GCS need to have the [GCS connector jar](https://cloud.google.com/dataproc/docs/concepts/connectors/cloud-storage#other_sparkhadoop_clusters) in their class path.
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Please read the [install instructions](https://github.com/GoogleCloudPlatform/bigdata-interop/blob/master/gcs/INSTALL.md)
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to properly set up the necessary libraries and configurations.
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One option is to place this jar in `${DRUID_HOME}/lib/` and `${DRUID_HOME}/extensions/druid-hdfs-storage/`.
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Finally, you need to configure the `core-site.xml` file with the filesystem
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and authentication properties needed for GCS. You may want to copy the below
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example properties. Please follow the instructions at
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[https://github.com/GoogleCloudPlatform/bigdata-interop/blob/master/gcs/INSTALL.md](https://github.com/GoogleCloudPlatform/bigdata-interop/blob/master/gcs/INSTALL.md)
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for more details.
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For more configurations, [GCS core default](https://github.com/GoogleCloudDataproc/hadoop-connectors/blob/v2.0.0/gcs/conf/gcs-core-default.xml)
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and [GCS core template](https://github.com/GoogleCloudDataproc/hadoop-connectors/blob/master/gcs/src/test/resources/core-site.xml).
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```xml
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<property>
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<name>fs.gs.impl</name>
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<value>com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystem</value>
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<description>The FileSystem for gs: (GCS) uris.</description>
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</property>
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<property>
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<name>fs.AbstractFileSystem.gs.impl</name>
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<value>com.google.cloud.hadoop.fs.gcs.GoogleHadoopFS</value>
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<description>The AbstractFileSystem for gs: uris.</description>
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</property>
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<property>
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<name>google.cloud.auth.service.account.enable</name>
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<value>true</value>
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<description>
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Whether to use a service account for GCS authorization.
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Setting this property to `false` will disable use of service accounts for
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authentication.
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</description>
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</property>
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<property>
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<name>google.cloud.auth.service.account.json.keyfile</name>
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<value>/path/to/keyfile</value>
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<description>
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The JSON key file of the service account used for GCS
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access when google.cloud.auth.service.account.enable is true.
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</description>
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</property>
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```
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## Reading data from HDFS or Cloud Storage
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### Native batch ingestion
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The [HDFS input source](../../ingestion/input-sources.md#hdfs-input-source) is supported by the [Parallel task](../../ingestion/native-batch.md)
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to read files directly from the HDFS Storage. You may be able to read objects from cloud storage
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with the HDFS input source, but we highly recommend to use a proper
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[Input Source](../../ingestion/input-sources.md) instead if possible because
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it is simple to set up. For now, only the [S3 input source](../../ingestion/input-sources.md#s3-input-source)
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and the [Google Cloud Storage input source](../../ingestion/input-sources.md#google-cloud-storage-input-source)
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are supported for cloud storage types, and so you may still want to use the HDFS input source
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to read from cloud storage other than those two.
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### Hadoop-based ingestion
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If you use the [Hadoop ingestion](../../ingestion/hadoop.md), you can read data from HDFS
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by specifying the paths in your [`inputSpec`](../../ingestion/hadoop.md#inputspec).
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See the [Static](../../ingestion/hadoop.md#static) inputSpec for details.
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