latest

Advanced Pinot Setup

Start Pinot components (scripts or docker images)

Set up Pinot by starting each component individually

Start Pinot Components using docker

Prerequisites

If running locally, ensure your docker cluster has enough resources, below is a sample config.

Pull Docker image

You can try out pre-built Pinot all-in-one Docker image.

export PINOT_VERSION=0.10.0
export PINOT_IMAGE=apachepinot/pinot:${PINOT_VERSION}
docker pull ${PINOT_IMAGE}

(Optional) You can also follow the instructions here to build your own images.

0. Create a network

Create an isolated bridge network in Docker.

docker network create -d bridge pinot-demo

1. Start Zookeeper

Start Zookeeper in daemon.

docker run \
    --network=pinot-demo \
    --name  pinot-zookeeper \
    --restart always \
    -p 2181:2181 \
    -d zookeeper:3.5.6

Start ZKUI to browse Zookeeper data at http://localhost:9090.

docker run \
    --network pinot-demo --name=zkui \
    -p 9090:9090 \
    -e ZK_SERVER=pinot-zookeeper:2181 \
    -d qnib/plain-zkui:latest

2. Start Pinot Controller

Start Pinot Controller in daemon and connect to Zookeeper.

docker run \
    --network=pinot-demo \
    --name pinot-controller \
    -p 9000:9000 \
    -d ${PINOT_IMAGE} StartController \
    -zkAddress pinot-zookeeper:2181

3. Start Pinot Broker

Start Pinot Broker in daemon and connect to Zookeeper.

docker run \
    --network=pinot-demo \
    --name pinot-broker \
    -d ${PINOT_IMAGE} StartBroker \
    -zkAddress pinot-zookeeper:2181

4. Start Pinot Server

Start Pinot Server in daemon and connect to Zookeeper.

export PINOT_IMAGE=apachepinot/pinot:0.3.0-SNAPSHOT
docker run \
    --network=pinot-demo \
    --name pinot-server \
    -d ${PINOT_IMAGE} StartServer \
    -zkAddress pinot-zookeeper:2181

Now all Pinot related components are started as an empty cluster.

You can run below command to check container status.

docker container ls -a

Sample Console Output

CONTAINER ID        IMAGE                              COMMAND                  CREATED              STATUS                PORTS                                                  NAMES
9e80c3fcd29b        apachepinot/pinot:0.3.0-SNAPSHOT   "./bin/pinot-admin.s…"   18 seconds ago       Up 17 seconds         8096-8099/tcp, 9000/tcp                                pinot-server
f4c42a5865c7        apachepinot/pinot:0.3.0-SNAPSHOT   "./bin/pinot-admin.s…"   21 seconds ago       Up 21 seconds         8096-8099/tcp, 9000/tcp                                pinot-broker
a413b0013806        apachepinot/pinot:0.3.0-SNAPSHOT   "./bin/pinot-admin.s…"   26 seconds ago       Up 25 seconds         8096-8099/tcp, 0.0.0.0:9000->9000/tcp                  pinot-controller
9d3b9c4d454b        zookeeper:3.5.6                    "/docker-entrypoint.…"   About a minute ago   Up About a minute     2888/tcp, 3888/tcp, 0.0.0.0:2181->2181/tcp, 8080/tcp   pinot-zookeeper

Start Pinot Using Config Files

Often times we need to customized the setup of Pinot components. Hence user can compile a config file and use it to start Pinot components.

Below are the examples config files and sample command to start Pinot.

Pinot Controller

Below is a sample pinot-controller.conf used in HelmChart setup.

controller.helix.cluster.name=pinot-quickstart
controller.port=9000
controller.vip.host=pinot-controller
controller.vip.port=9000
controller.data.dir=/var/pinot/controller/data
controller.zk.str=pinot-zookeeper:2181
pinot.set.instance.id.to.hostname=true

In order to run Pinot Controller, the command is:

bin/pinot-admin.sh StartController -configFileName config/pinot-controller.conf

Configure Controller

Below are some configurations you can set in Pinot Controller. You can head over to Controller for complete list of available configs.

Pinot Broker

Below is a sample pinot-broker.conf used in HelmChart setup.

pinot.broker.client.queryPort=8099
pinot.broker.routing.table.builder.class=random
pinot.set.instance.id.to.hostname=true

In order to run Pinot Broker, the command is:

bin/pinot-admin.sh StartBroker -clusterName pinot-quickstart -zkAddress pinot-zookeeper:2181 -configFileName config/pinot-broker.conf

Configure Broker

Below are some configurations you can set in Pinot Broker. You can head over to Broker for complete list of available configs.

Pinot Server

Below is a sample pinot-server.conf used in HelmChart setup.

pinot.server.netty.port=8098
pinot.server.adminapi.port=8097
pinot.server.instance.dataDir=/var/pinot/server/data/index
pinot.server.instance.segmentTarDir=/var/pinot/server/data/segment
pinot.set.instance.id.to.hostname=true

In order to run Pinot Server, the command is:

bin/pinot-admin.sh StartServer -clusterName pinot-quickstart -zkAddress pinot-zookeeper:2181 -configFileName config/pinot-server.conf

Configure Server

Below are some outstanding configurations you can set in Pinot Server. You can head over to Server for complete list of available configs.

Create and Configure table

A TABLE in regular database world is represented as <TABLE>_OFFLINE and/or <TABLE>_REALTIME in Pinot depending on the ingestion mode (batch, real-time, hybrid)

See examples for all possible batch/streaming tables.

Batch Table Creation

See Batch Tables for table configuration details and how to customize it.

docker run \
    --network=pinot-demo \
    --name pinot-batch-table-creation \
    ${PINOT_IMAGE} AddTable \
    -schemaFile examples/batch/airlineStats/airlineStats_schema.json \
    -tableConfigFile examples/batch/airlineStats/airlineStats_offline_table_config.json \
    -controllerHost pinot-controller \
    -controllerPort 9000 \
    -exec

Sample Console Output

Executing command: AddTable -tableConfigFile examples/batch/airlineStats/airlineStats_offline_table_config.json -schemaFile examples/batch/airlineStats/airlineStats_schema.json -controllerHost pinot-controller -controllerPort 9000 -exec
Sending request: http://pinot-controller:9000/schemas to controller: a413b0013806, version: Unknown
{"status":"Table airlineStats_OFFLINE succesfully added"}

Automatically add an inverted index to your batch table

By default, the inverted index type is the only type of index that isn't created automatically during segment generation. Instead, they are generated when the segments are loaded on the server. But, waiting to build indexes until load time increases the startup time and takes up resources with every new segment push, which increases the time for other operations such as rebalance.

To automatically create an inverted index during segment generation, add an entry to your table index config in the table configuration file.

This setting works with batch (offline) tables.

When set to true, Pinot creates an inverted index for the columns that you specify in the invertedIndexColumns list in the table configuration.

This setting is false by default.

Set createInvertedIndexDuringSegmentGeneration to true in your table config, as follows:

...
"tableIndexConfig": {
    ...
    "createInvertedIndexDuringSegmentGeneration": true,
    ...
}
...

When you update this setting in your table configuration, you must reload the table segment to apply the inverted index to all existing segments.

Streaming Table Creation

See Streaming Tables for table configuration details and how to customize it.

Start Kafka

docker run \
    --network pinot-demo --name=kafka \
    -e KAFKA_ZOOKEEPER_CONNECT=pinot-zookeeper:2181/kafka \
    -e KAFKA_BROKER_ID=0 \
    -e KAFKA_ADVERTISED_HOST_NAME=kafka \
    -d wurstmeister/kafka:latest

Create a Kafka Topic

docker exec \
  -t kafka \
  /opt/kafka/bin/kafka-topics.sh \
  --zookeeper pinot-zookeeper:2181/kafka \
  --partitions=1 --replication-factor=1 \
  --create --topic flights-realtime

Create a Streaming table

docker run \
    --network=pinot-demo \
    --name pinot-streaming-table-creation \
    ${PINOT_IMAGE} AddTable \
    -schemaFile examples/stream/airlineStats/airlineStats_schema.json \
    -tableConfigFile examples/docker/table-configs/airlineStats_realtime_table_config.json \
    -controllerHost pinot-controller \
    -controllerPort 9000 \
    -exec

Sample output

Executing command: AddTable -tableConfigFile examples/docker/table-configs/airlineStats_realtime_table_config.json -schemaFile examples/stream/airlineStats/airlineStats_schema.json -controllerHost pinot-controller -controllerPort 9000 -exec
Sending request: http://pinot-controller:9000/schemas to controller: 8fbe601012f3, version: Unknown
{"status":"Table airlineStats_REALTIME succesfully added"}

Use sortedColumn with streaming tables

For streaming tables, you can use a sorted index with sortedColumn to sort data when generating segments as the segment is created. See Real-time tables for more information.

A sorted forward index can be used as an inverted index with better performance, but with the limitation that the search is only applied to one column per table. See Sorted inverted index to learn more.

Load Data

Now that the table is configured, let's load some data. Data can be loaded in batch mode or streaming mode. See ingestion overview page for details. Loading data involves generating pinot segments from raw data and pushing them to the pinot cluster.

Load Data in Batch

User can always generate and push segments to Pinot via standalone scripts or using frameworks such as Hadoop or Spark. See this page for more details on setting up Data Ingestion Jobs.

Below example goes with the standalone mode.

docker run \
    --network=pinot-demo \
    --name pinot-data-ingestion-job \
    ${PINOT_IMAGE} LaunchDataIngestionJob \
    -jobSpecFile examples/docker/ingestion-job-specs/airlineStats.yaml

Sample Console Output

SegmentGenerationJobSpec:
!!org.apache.pinot.spi.ingestion.batch.spec.SegmentGenerationJobSpec
excludeFileNamePattern: null
executionFrameworkSpec: {extraConfigs: null, name: standalone, segmentGenerationJobRunnerClassName: org.apache.pinot.plugin.ingestion.batch.standalone.SegmentGenerationJobRunner,
  segmentTarPushJobRunnerClassName: org.apache.pinot.plugin.ingestion.batch.standalone.SegmentTarPushJobRunner,
  segmentUriPushJobRunnerClassName: org.apache.pinot.plugin.ingestion.batch.standalone.SegmentUriPushJobRunner}
includeFileNamePattern: glob:**/*.avro
inputDirURI: examples/batch/airlineStats/rawdata
jobType: SegmentCreationAndTarPush
outputDirURI: examples/batch/airlineStats/segments
overwriteOutput: true
pinotClusterSpecs:
- {controllerURI: 'http://pinot-controller:9000'}
pinotFSSpecs:
- {className: org.apache.pinot.spi.filesystem.LocalPinotFS, configs: null, scheme: file}
pushJobSpec: {pushAttempts: 2, pushParallelism: 1, pushRetryIntervalMillis: 1000,
  segmentUriPrefix: null, segmentUriSuffix: null}
recordReaderSpec: {className: org.apache.pinot.plugin.inputformat.avro.AvroRecordReader,
  configClassName: null, configs: null, dataFormat: avro}
segmentNameGeneratorSpec: null
tableSpec: {schemaURI: 'http://pinot-controller:9000/tables/airlineStats/schema',
  tableConfigURI: 'http://pinot-controller:9000/tables/airlineStats', tableName: airlineStats}

Trying to create instance for class org.apache.pinot.plugin.ingestion.batch.standalone.SegmentGenerationJobRunner
Initializing PinotFS for scheme file, classname org.apache.pinot.spi.filesystem.LocalPinotFS
Finished building StatsCollector!
Collected stats for 403 documents
Created dictionary for INT column: FlightNum with cardinality: 386, range: 14 to 7389
Using fixed bytes value dictionary for column: Origin, size: 294
Created dictionary for STRING column: Origin with cardinality: 98, max length in bytes: 3, range: ABQ to VPS
Created dictionary for INT column: Quarter with cardinality: 1, range: 1 to 1
Created dictionary for INT column: LateAircraftDelay with cardinality: 50, range: -2147483648 to 303
......
......
Pushing segment: airlineStats_OFFLINE_16085_16085_29 to location: http://pinot-controller:9000 for table airlineStats
Sending request: http://pinot-controller:9000/v2/segments?tableName=airlineStats to controller: a413b0013806, version: Unknown
Response for pushing table airlineStats segment airlineStats_OFFLINE_16085_16085_29 to location http://pinot-controller:9000 - 200: {"status":"Successfully uploaded segment: airlineStats_OFFLINE_16085_16085_29 of table: airlineStats"}
Pushing segment: airlineStats_OFFLINE_16084_16084_30 to location: http://pinot-controller:9000 for table airlineStats
Sending request: http://pinot-controller:9000/v2/segments?tableName=airlineStats to controller: a413b0013806, version: Unknown
Response for pushing table airlineStats segment airlineStats_OFFLINE_16084_16084_30 to location http://pinot-controller:9000 - 200: {"status":"Successfully uploaded segment: airlineStats_OFFLINE_16084_16084_30 of table: airlineStats"}

JobSpec yaml file has all the information regarding data format, input data location and pinot cluster coordinates. Note that this assumes that the controller is RUNNING to fetch the table config and schema. If not, you will have to configure the spec to point at their location. See Pinot Ingestion Job for more details.

Load Data in Streaming

Kafka

Run below command to stream JSON data into Kafka topic: flights-realtime

docker run \
  --network pinot-demo \
  --name=loading-airlineStats-data-to-kafka \
  ${PINOT_IMAGE} StreamAvroIntoKafka \
  -avroFile examples/stream/airlineStats/sample_data/airlineStats_data.avro \
  -kafkaTopic flights-realtime -kafkaBrokerList kafka:9092 -zkAddress pinot-zookeeper:2181/kafka
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