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Use S3 and Pinot in Docker

Setup Pinot Cluster

In order to setup Pinot in Docker to use S3 as deep store, we need to put extra configs for Controller and Server.

Create a docker network

Start Zookeeper

Prepare Pinot configuration files

Below sections will prepare 3 config files under /tmp/pinot-s3-docker to mount to the container.

Start Controller

Below is a sample controller.conf file.

Please config:

controller.data.dirto your s3 bucket. All the uploaded segments will be stored there.

And add s3 as a pinot storage with configs:

Regarding AWS Credential, we also follow the convention of .

You can specify AccessKey and Secret using:

  • Environment Variables - AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY

Add s3 to pinot.controller.segment.fetcher.protocols

and set pinot.controller.segment.fetcher.s3.class toorg.apache.pinot.common.utils.fetcher.PinotFSSegmentFetcher

Then start pinot controller with:

Start Broker

Broker is a simple one you can just start it with default:

Start Server

Below is a sample server.conf file

Similar to controller config, please also set s3 configs in pinot server.

Then start pinot server with:

Setup Table

In this demo, we just use airlineStats table as an example which is already packaged inside the docker image.

You can also mount your table conf and schema files to the container and run it.

Set up Ingestion Jobs

Standalone Job

Below is a sample standalone ingestion job spec with certain notable changes:

  • jobType is SegmentCreationAndMetadataPush (this job will bypass controller download segment )

  • inputDirURI is set to a s3 location s3://my.bucket/batch/airlineStats/rawdata/

  • outputDirURI is set to a s3 location s3://my.bucket/output/airlineStats/segments

Sample ingestionJobSpec.yaml

Launch the data ingestion job:

docker network create -d bridge pinot-demo
(RECOMMENDED since they are recognized by all the AWS SDKs and CLI except for .NET), or
AWS_ACCESS_KEY
and
AWS_SECRET_KEY
(only recognized by Java SDK)
  • Java System Properties - aws.accessKeyId and aws.secretKey

  • Credential profiles file at the default location (~/.aws/credentials) shared by all AWS SDKs and the AWS CLI

  • Configure AWS credential in pinot config files, e.g. set pinot.controller.storage.factory.s3.accessKey and pinot.controller.storage.factory.s3.secretKey in the config file. (Not recommended)

  • Add a new PinotFs under pinotFSSpecs

    DefaultAWSCredentialsProviderChain
    - scheme: s3
      className: org.apache.pinot.plugin.filesystem.S3PinotFS
      configs:
        region: 'us-west-2'
    docker run \
        --name zookeeper \
        --restart always \
        --network=pinot-demo \
        -d zookeeper:3.5.6
    /tmp/pinot-s3-docker/
                         controller.conf
                         server.conf
                         ingestionJobSpec.yaml
    pinot.controller.storage.factory.class.s3=org.apache.pinot.plugin.filesystem.S3PinotFS
    pinot.controller.storage.factory.s3.region=us-west-2
    pinot.role=controller
    pinot.controller.storage.factory.class.s3=org.apache.pinot.plugin.filesystem.S3PinotFS
    pinot.controller.storage.factory.s3.region=us-west-2
    controller.data.dir=s3://<my-bucket>/pinot-data/pinot-s3-example-docker/controller-data/
    controller.local.temp.dir=/tmp/pinot-tmp-data/
    controller.helix.cluster.name=pinot-s3-example-docker
    controller.zk.str=zookeeper:2181
    controller.port=9000
    controller.enable.split.commit=true
    pinot.controller.segment.fetcher.protocols=file,http,s3
    pinot.controller.segment.fetcher.s3.class=org.apache.pinot.common.utils.fetcher.PinotFSSegmentFetcher
    docker run --rm -ti \
        --name pinot-controller \
        --network=pinot-demo \
        -p 9000:9000 \
        --env AWS_ACCESS_KEY_ID=<aws-access-key-id> \
        --env AWS_SECRET_ACCESS_KEY=<aws-secret-access-key> \
        --mount type=bind,source=/tmp/pinot-s3-docker,target=/tmp \
        apachepinot/pinot:0.6.0-SNAPSHOT-ca8545b29-20201105-jdk11 StartController \
        -configFileName /tmp/controller.conf
    docker run --rm -ti \
        --name pinot-broker \
        --network=pinot-demo \
        --env AWS_ACCESS_KEY_ID=<aws-access-key-id> \
        --env AWS_SECRET_ACCESS_KEY=<aws-secret-access-key> \
        apachepinot/pinot:0.6.0-SNAPSHOT-ca8545b29-20201105-jdk11 StartBroker \
        -zkAddress zookeeper:2181 -clusterName pinot-s3-example-docker
    pinot.server.netty.port=8098
    pinot.server.adminapi.port=8097
    pinot.server.instance.dataDir=/tmp/pinot-tmp/server/index
    pinot.server.instance.segmentTarDir=/tmp/pinot-tmp/server/segmentTars
    
    
    pinot.server.storage.factory.class.s3=org.apache.pinot.plugin.filesystem.S3PinotFS
    pinot.server.storage.factory.s3.region=us-west-2
    pinot.server.segment.fetcher.protocols=file,http,s3
    pinot.server.segment.fetcher.s3.class=org.apache.pinot.common.utils.fetcher.PinotFSSegmentFetcher
    docker run --rm -ti \
        --name pinot-server \
        --network=pinot-demo \
        --env AWS_ACCESS_KEY_ID=<aws-access-key-id> \
        --env AWS_SECRET_ACCESS_KEY=<aws-secret-access-key> \
        --mount type=bind,source=/tmp/pinot-s3-docker,target=/tmp \
        apachepinot/pinot:0.6.0-SNAPSHOT-ca8545b29-20201105-jdk11 StartServer \
        -zkAddress zookeeper:2181 -clusterName pinot-s3-example-docker \
        -configFileName /tmp/server.conf
    docker run --rm -ti \
        --name pinot-ingestion-job \
        --network=pinot-demo \
        apachepinot/pinot:0.6.0-SNAPSHOT-ca8545b29-20201105-jdk11 AddTable \
        -controllerHost pinot-controller \
        -controllerPort 9000 \
        -schemaFile examples/batch/airlineStats/airlineStats_schema.json \
        -tableConfigFile examples/batch/airlineStats/airlineStats_offline_table_config.json \
        -exec
    # executionFrameworkSpec: Defines ingestion jobs to be running.
    executionFrameworkSpec:
    
      # name: execution framework name
      name: 'standalone'
    
      # segmentGenerationJobRunnerClassName: class name implements org.apache.pinot.spi.batch.ingestion.runner.SegmentGenerationJobRunner interface.
      segmentGenerationJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.standalone.SegmentGenerationJobRunner'
    
      # segmentTarPushJobRunnerClassName: class name implements org.apache.pinot.spi.batch.ingestion.runner.SegmentTarPushJobRunner interface.
      segmentTarPushJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.standalone.SegmentTarPushJobRunner'
    
      # segmentUriPushJobRunnerClassName: class name implements org.apache.pinot.spi.batch.ingestion.runner.SegmentUriPushJobRunner interface.
      segmentUriPushJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.standalone.SegmentUriPushJobRunner'
    
      # segmentMetadataPushJobRunnerClassName: class name implements org.apache.pinot.spi.batch.ingestion.runner.IngestionJobRunner interface.
      segmentMetadataPushJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.standalone.SegmentMetadataPushJobRunner'
    
    # jobType: Pinot ingestion job type.
    # Supported job types are:
    #   'SegmentCreation'
    #   'SegmentTarPush'
    #   'SegmentUriPush'
    #   'SegmentCreationAndTarPush'
    #   'SegmentCreationAndUriPush'
    jobType: SegmentCreationAndMetadataPush
    
    # inputDirURI: Root directory of input data, expected to have scheme configured in PinotFS.
    inputDirURI: 's3://<my-bucket>/pinot-data/rawdata/airlineStats/rawdata/'
    
    # includeFileNamePattern: include file name pattern, supported glob pattern.
    # Sample usage:
    #   'glob:*.avro' will include all avro files just under the inputDirURI, not sub directories;
    #   'glob:**/*.avro' will include all the avro files under inputDirURI recursively.
    includeFileNamePattern: 'glob:**/*.avro'
    
    # excludeFileNamePattern: exclude file name pattern, supported glob pattern.
    # Sample usage:
    #   'glob:*.avro' will exclude all avro files just under the inputDirURI, not sub directories;
    #   'glob:**/*.avro' will exclude all the avro files under inputDirURI recursively.
    # _excludeFileNamePattern: ''
    
    # outputDirURI: Root directory of output segments, expected to have scheme configured in PinotFS.
    outputDirURI: 's3://<my-bucket>/pinot-data/pinot-s3-docker/segments/airlineStats'
    
    # segmentCreationJobParallelism: The parallelism to create egments.
    segmentCreationJobParallelism: 5
    
    # overwriteOutput: Overwrite output segments if existed.
    overwriteOutput: true
    
    # pinotFSSpecs: defines all related Pinot file systems.
    pinotFSSpecs:
    
      - # scheme: used to identify a PinotFS.
        # E.g. local, hdfs, dbfs, etc
        scheme: file
    
        # className: Class name used to create the PinotFS instance.
        # E.g.
        #   org.apache.pinot.spi.filesystem.LocalPinotFS is used for local filesystem
        #   org.apache.pinot.plugin.filesystem.AzurePinotFS is used for Azure Data Lake
        #   org.apache.pinot.plugin.filesystem.HadoopPinotFS is used for HDFS
        className: org.apache.pinot.spi.filesystem.LocalPinotFS
    
    
      - scheme: s3
        className: org.apache.pinot.plugin.filesystem.S3PinotFS
        configs:
          region: 'us-west-2'
    
    # recordReaderSpec: defines all record reader
    recordReaderSpec:
    
      # dataFormat: Record data format, e.g. 'avro', 'parquet', 'orc', 'csv', 'json', 'thrift' etc.
      dataFormat: 'avro'
    
      # className: Corresponding RecordReader class name.
      # E.g.
      #   org.apache.pinot.plugin.inputformat.avro.AvroRecordReader
      #   org.apache.pinot.plugin.inputformat.csv.CSVRecordReader
      #   org.apache.pinot.plugin.inputformat.parquet.ParquetRecordReader
      #   org.apache.pinot.plugin.inputformat.json.JSONRecordReader
      #   org.apache.pinot.plugin.inputformat.orc.ORCRecordReader
      #   org.apache.pinot.plugin.inputformat.thrift.ThriftRecordReader
      className: 'org.apache.pinot.plugin.inputformat.avro.AvroRecordReader'
    
    # tableSpec: defines table name and where to fetch corresponding table config and table schema.
    tableSpec:
    
      # tableName: Table name
      tableName: 'airlineStats'
    
      # schemaURI: defines where to read the table schema, supports PinotFS or HTTP.
      # E.g.
      #   hdfs://path/to/table_schema.json
      #   http://localhost:9000/tables/myTable/schema
      schemaURI: 'http://pinot-controller:9000/tables/airlineStats/schema'
    
      # tableConfigURI: defines where to reade the table config.
      # Supports using PinotFS or HTTP.
      # E.g.
      #   hdfs://path/to/table_config.json
      #   http://localhost:9000/tables/myTable
      # Note that the API to read Pinot table config directly from pinot controller contains a JSON wrapper.
      # The real table config is the object under the field 'OFFLINE'.
      tableConfigURI: 'http://pinot-controller:9000/tables/airlineStats'
    
    # pinotClusterSpecs: defines the Pinot Cluster Access Point.
    pinotClusterSpecs:
      - # controllerURI: used to fetch table/schema information and data push.
        # E.g. http://localhost:9000
        controllerURI: 'http://pinot-controller:9000'
    
    # pushJobSpec: defines segment push job related configuration.
    pushJobSpec:
    
      # pushAttempts: number of attempts for push job, default is 1, which means no retry.
      pushAttempts: 2
    
      # pushRetryIntervalMillis: retry wait Ms, default to 1 second.
      pushRetryIntervalMillis: 1000
    
    docker run --rm -ti \
        --name pinot-ingestion-job \
        --network=pinot-demo \
        --env AWS_ACCESS_KEY_ID=<aws-access-key-id> \
        --env AWS_SECRET_ACCESS_KEY=<aws-secret-access-key> \
        --mount type=bind,source=/tmp/pinot-s3-docker,target=/tmp \
        apachepinot/pinot:0.6.0-SNAPSHOT-ca8545b29-20201105-jdk11 LaunchDataIngestionJob \
        -jobSpecFile /tmp/ingestionJobSpec.yaml
    pinot.controller.storage.factory.s3.accessKey=****************LFVX
    pinot.controller.storage.factory.s3.secretKey=****************gfhz