Quick Start Examples

This section describes quick start commands that launch all Pinot components in a single process.

Pinot ships with QuickStart commands that launch Pinot components in a single process and import pre-built datasets. These quick start examples are a good place if you're just getting started with Pinot. The examples begin with the Batch Processing example, after the following notes:

  • Prerequisites

    You must have either installed Pinot locally or have Docker installed if you want to use the Pinot Docker image. The examples are available in each option and work the same. The decision of which to choose depends on your installation preference and how you generally like to work. If you don't know which to choose, using Docker will make your cleanup easier after you are done with the examples.

  • Pinot versions in examples

    The Docker-based examples on this page use pinot:latest, which instructs Docker to pull and use the most recent release of Apache Pinot. If you prefer to use a specific release instead, you can designate it by replacing latest with the release number, like this: pinot:0.12.1.

    The local install-based examples that are run using the launcher scripts will use the Apache Pinot version you installed.

  • Stopping a running example

    To stop a running example, enter Ctrl+C in the same terminal where you ran the docker run command to start the example.

macOS Monterey Users

By default the Airplay receiver server runs on port 7000, which is also the port used by the Pinot Server in the Quick Start. You may see the following error when running these examples:

Failed to start a Pinot [SERVER]
java.lang.RuntimeException: java.net.BindException: Address already in use
	at org.apache.pinot.core.transport.QueryServer.start(QueryServer.java:103) ~[pinot-all-0.9.0-jar-with-dependencies.jar:0.9.0-cf8b84e8b0d6ab62374048de586ce7da21132906]
	at org.apache.pinot.server.starter.ServerInstance.start(ServerInstance.java:158) ~[pinot-all-0.9.0-jar-with-dependencies.jar:0.9.0-cf8b84e8b0d6ab62374048de586ce7da21132906]
	at org.apache.helix.manager.zk.ParticipantManager.handleNewSession(ParticipantManager.java:110) ~[pinot-all-0.9.0-jar-with-dependencies.jar:0.9.0-cf8b84e8b0d6ab62374048de586ce7da2113

If you disable the Airplay receiver server and try again, you shouldn't see this error message anymore.

Batch Processing

This example demonstrates how to do batch processing with Pinot. The command:

  • Starts Apache Zookeeper, Pinot Controller, Pinot Broker, and Pinot Server.

  • Creates the baseballStats table

  • Launches a standalone data ingestion job that builds one segment for a given CSV data file for the baseballStats table and pushes the segment to the Pinot Controller.

  • Issues sample queries to Pinot

docker run \
    -p 9000:9000 \
    apachepinot/pinot:latest QuickStart \
    -type batch

Batch JSON

This example demonstrates how to import and query JSON documents in Pinot. The command:

  • Starts Apache Zookeeper, Pinot Controller, Pinot Broker, and Pinot Server.

  • Creates the githubEvents table

  • Launches a standalone data ingestion job that builds one segment for a given JSON data file for the githubEvents table and pushes the segment to the Pinot Controller.

  • Issues sample queries to Pinot

docker run \
    -p 9000:9000 \
    apachepinot/pinot:latest QuickStart \
    -type batch_json_index

Batch with complex data types

This example demonstrates how to do batch processing in Pinot where the the data items have complex fields that need to be unnested. The command:

  • Starts Apache Zookeeper, Pinot Controller, Pinot Broker, and Pinot Server.

  • Creates the githubEvents table

  • Launches a standalone data ingestion job that builds one segment for a given JSON data file for the githubEvents table and pushes the segment to the Pinot Controller.

  • Issues sample queries to Pinot

docker run \
    -p 9000:9000 \
    apachepinot/pinot:latest QuickStart \
    -type batch_complex_type

Streaming

This example demonstrates how to do stream processing with Pinot. The command:

  • Starts Apache Kafka, Apache Zookeeper, Pinot Controller, Pinot Broker, and Pinot Server.

  • Creates meetupRsvp table

  • Launches a meetup stream

  • Publishes data to a Kafka topic meetupRSVPEvents that is subscribed to by Pinot.

  • Issues sample queries to Pinot

docker run \
    -p 9000:9000 \
    apachepinot/pinot:latest QuickStart \
    -type stream

Streaming JSON

This example demonstrates how to do stream processing with JSON documents in Pinot. The command:

  • Starts Apache Kafka, Apache Zookeeper, Pinot Controller, Pinot Broker, and Pinot Server.

  • Creates meetupRsvp table

  • Launches a meetup stream

  • Publishes data to a Kafka topic meetupRSVPEvents that is subscribed to by Pinot

  • Issues sample queries to Pinot

docker run \
    -p 9000:9000 \
    apachepinot/pinot:latest QuickStart \
    -type stream_json_index

Streaming with minion cleanup

This example demonstrates how to do stream processing in Pinot with RealtimeToOfflineSegmentsTask and MergeRollupTask minion tasks continuously optimizing segments as data gets ingested. The command:

  • Starts Apache Kafka, Apache Zookeeper, Pinot Controller, Pinot Broker, Pinot Minion, and Pinot Server.

  • Creates githubEvents table

  • Launches a GitHub events stream

  • Publishes data to a Kafka topic githubEvents that is subscribed to by Pinot.

  • Issues sample queries to Pinot

docker run \
    -p 9000:9000 \
    apachepinot/pinot:latest QuickStart \
    -type realtime_minion

Streaming with complex data types

This example demonstrates how to do stream processing in Pinot where the stream contains items that have complex fields that need to be unnested. The command:

  • Starts Apache Kafka, Apache Zookeeper, Pinot Controller, Pinot Broker, Pinot Minion, and Pinot Server.

  • Creates meetupRsvp table

  • Launches a meetup stream

  • Publishes data to a Kafka topic meetupRSVPEvents that is subscribed to by Pinot.

  • Issues sample queries to Pinot

docker run \
    -p 9000:9000 \
    apachepinot/pinot:latest QuickStart \
    -type stream_complex_type

Upsert

This example demonstrates how to do stream processing with upsert with Pinot. The command:

  • Starts Apache Kafka, Apache Zookeeper, Pinot Controller, Pinot Broker, and Pinot Server.

  • Creates meetupRsvp table

  • Launches a meetup stream

  • Publishes data to a Kafka topic meetupRSVPEvents that is subscribed to by Pinot

  • Issues sample queries to Pinot

docker run \
    -p 9000:9000 \
    apachepinot/pinot:latest QuickStart \
    -type upsert

Upsert JSON

This example demonstrates how to do stream processing with upsert with JSON documents in Pinot. The command:

  • Starts Apache Kafka, Apache Zookeeper, Pinot Controller, Pinot Broker, and Pinot Server.

  • Creates meetupRsvp table

  • Launches a meetup stream

  • Publishes data to a Kafka topic meetupRSVPEvents that is subscribed to by Pinot

  • Issues sample queries to Pinot

docker run \
    -p 9000:9000 \
    apachepinot/pinot:latest QuickStart \
    -type upsert_json_index

Hybrid

This example demonstrates how to do hybrid stream and batch processing with Pinot. The command:

  1. Starts Apache Kafka, Apache Zookeeper, Pinot Controller, Pinot Broker, and Pinot Server.

  2. Creates airlineStats table

  3. Launches a standalone data ingestion job that builds segments under a given directory of Avro files for the airlineStats table and pushes the segments to the Pinot Controller.

  4. Launches a stream of flights stats

  5. Publishes data to a Kafka topic airlineStatsEvents that is subscribed to by Pinot.

  6. Issues sample queries to Pinot

docker run \
    -p 9000:9000 \
    apachepinot/pinot:latest QuickStart \
    -type hybrid

Join

This example demonstrates how to do joins in Pinot using the Lookup UDF. The command:

  • Starts Apache Zookeeper, Pinot Controller, Pinot Broker, and Pinot Server in the same container.

  • Creates the baseballStats table

  • Launches a data ingestion job that builds one segment for a given CSV data file for the baseballStats table and pushes the segment to the Pinot Controller.

  • Creates the dimBaseballTeams table

  • Launches a data ingestion job that builds one segment for a given CSV data file for the dimBaseballStats table and pushes the segment to the Pinot Controller.

  • Issues sample queries to Pinot

docker run \
    -p 9000:9000 \
    apachepinot/pinot:latest QuickStart \
    -type join
PreviousRunning Pinot in DockerNextRunning in Kubernetes

Last updated

Was this helpful?