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Ingest streaming data from Apache Kafka

This guide shows you how to ingest a stream of records from an Apache Kafka topic into a Pinot table.

Learn how to ingest data from Kafka, a stream processing platform. You should have a local cluster up and running, following the instructions in Set up a cluster.

Install and Launch Kafka

Let's start by downloading Kafka to our local machine.

To pull down the latest Docker image, run the following command:

docker pull wurstmeister/kafka:latest

Download Kafka from and then extract it:

Next we'll spin up a Kafka broker:

Note: The --network pinot-demo flag is optional and assumes that you have a Docker network named pinot-demo that you want to connect the Kafka container to.

On one terminal window run this command:

Start Zookeeper

And on another window, run this command:

Start Kafka Broker

Data Source

We're going to generate some JSON messages from the terminal using the following script:

datagen.py

If you run this script (python datagen.py), you'll see the following output:

Ingesting Data into Kafka

Let's now pipe that stream of messages into Kafka, by running the following command:

We can check how many messages have been ingested by running the following command:

Output

And we can print out the messages themselves by running the following command

Output

Schema

A schema defines what fields are present in the table along with their data types in JSON format.

Create a file called /tmp/pinot/schema-stream.json and add the following content to it.

Table Config

A table is a logical abstraction that represents a collection of related data. It is composed of columns and rows (known as documents in Pinot). The table config defines the table's properties in JSON format.

Create a file called /tmp/pinot/table-config-stream.json and add the following content to it.

Create schema and table

Create the table and schema by running the appropriate command below:

Querying

Navigate to and click on the events table to run a query that shows the first 10 rows in this table.

Querying the events table

Kafka ingestion guidelines

Kafka versions in Pinot

Pinot supports two versions of the Kafka library: kafka-0.9 and kafka-2.x for low level consumers.

Post release 0.10.0, we have started shading kafka packages inside Pinot. If you are using our latest tagged docker images or master build, you should replace org.apache.kafka with shaded.org.apache.kafka in your table config.

Upgrade from Kafka 0.9 connector to Kafka 2.x connector

Update table config for low level consumer: stream.kafka.consumer.factory.class.name from org.apache.pinot.core.realtime.impl.kafka.KafkaConsumerFactory to org.apache.pinot.core.realtime.impl.kafka2.KafkaConsumerFactory.

Pinot does not support using high-level Kafka consumers (HLC). Pinot uses low-level consumers to ensure accurate results, supports operational complexity and scalability, and minimizes storage overhead.

How to consume from a Kafka version > 2.0.0

This connector is also suitable for Kafka lib version higher than 2.0.0. In , change the kafka.lib.version from 2.0.0 to 2.1.1 will make this Connector working with Kafka 2.1.1.

Kafka configurations in Pinot

Use Kafka partition (low) level consumer with SSL

Here is an example config which uses SSL based authentication to talk with kafka and schema-registry. Notice there are two sets of SSL options, ones starting with ssl. are for kafka consumer and ones with stream.kafka.decoder.prop.schema.registry. are for SchemaRegistryClient used by KafkaConfluentSchemaRegistryAvroMessageDecoder.

Consume transactionally-committed messages

The connector with Kafka library 2.0+ supports Kafka transactions. The transaction support is controlled by config kafka.isolation.level in Kafka stream config, which can be read_committed or read_uncommitted (default). Setting it to read_committed will ingest transactionally committed messages in Kafka stream only.

For example,

Note that the default value of this config read_uncommitted to read all messages. Also, this config supports low-level consumer only.

Use Kafka partition (low) level consumer with SASL_SSL

Here is an example config which uses SASL_SSL based authentication to talk with kafka and schema-registry. Notice there are two sets of SSL options, some for kafka consumer and ones with stream.kafka.decoder.prop.schema.registry. are for SchemaRegistryClient used by KafkaConfluentSchemaRegistryAvroMessageDecoder.

Extract record headers as Pinot table columns

Pinot's Kafka connector supports automatically extracting record headers and metadata into the Pinot table columns. The following table shows the mapping for record header/metadata to Pinot table column names:

Kafka Record

Pinot Table Column

Description

In order to enable the metadata extraction in a Kafka table, you can set the stream config metadata.populate to true.

In addition to this, if you want to use any of these columns in your table, you have to list them explicitly in your table's schema.

For example, if you want to add only the offset and key as dimension columns in your Pinot table, it can listed in the schema as follows:

Once the schema is updated, these columns are similar to any other pinot column. You can apply ingestion transforms and / or define indexes on them.

Remember to follow the when updating schema of an existing table!

Tell Pinot where to find an Avro schema

There is a standalone utility to generate the schema from an Avro file. See [infer the pinot schema from the avro schema and JSON data]() for details.

To avoid errors like The Avro schema must be provided, designate the location of the schema in your streamConfigs section. For example, if your current section contains the following:

Then add this key: "stream.kafka.decoder.prop.schema"followed by a value that denotes the location of your schema.

Ingest streaming data from Apache Kafka

This guide shows you how to ingest a stream of records from an Apache Kafka topic into a Pinot table.

Learn how to ingest data from Kafka, a stream processing platform. You should have a local cluster up and running, following the instructions in Set up a cluster.

Install and Launch Kafka

Let's start by downloading Kafka to our local machine.

To pull down the latest Docker image, run the following command:

docker pull wurstmeister/kafka:latest

Download Kafka from and then extract it:

Next we'll spin up a Kafka broker:

Note: The --network pinot-demo flag is optional and assumes that you have a Docker network named pinot-demo that you want to connect the Kafka container to.

On one terminal window run this command:

Start Zookeeper

And on another window, run this command:

Start Kafka Broker

Data Source

We're going to generate some JSON messages from the terminal using the following script:

datagen.py

If you run this script (python datagen.py), you'll see the following output:

Ingesting Data into Kafka

Let's now pipe that stream of messages into Kafka, by running the following command:

We can check how many messages have been ingested by running the following command:

Output

And we can print out the messages themselves by running the following command

Output

Schema

A schema defines what fields are present in the table along with their data types in JSON format.

Create a file called /tmp/pinot/schema-stream.json and add the following content to it.

Table Config

Create a file called /tmp/pinot/table-config-stream.json and add the following content to it.

Create schema and table

Create the table and schema by running the appropriate command below:

Querying

Navigate to and click on the events table to run a query that shows the first 10 rows in this table.

Querying the events table

Kafka ingestion guidelines

Kafka versions in Pinot

Pinot supports two versions of the Kafka library: kafka-0.9 and kafka-2.x for low level consumers.

Upgrade from Kafka 0.9 connector to Kafka 2.x connector

Update table config for low level consumer: stream.kafka.consumer.factory.class.name from org.apache.pinot.core.realtime.impl.kafka.KafkaConsumerFactory to org.apache.pinot.core.realtime.impl.kafka2.KafkaConsumerFactory.

How to consume from a Kafka version > 2.0.0

This connector is also suitable for Kafka lib version higher than 2.0.0. In , change the kafka.lib.version from 2.0.0 to 2.1.1 will make this Connector working with Kafka 2.1.1.

Kafka configurations in Pinot

Use Kafka partition (low) level consumer with SSL

Consume transactionally-committed messages

For example,

Note that the default value of this config read_uncommitted to read all messages. Also, this config supports low-level consumer only.

Use Kafka partition (low) level consumer with SASL_SSL

Extract record headers as Pinot table columns

Kafka Record

Pinot Table Column

Description

In order to enable the metadata extraction in a Kafka table, you can set the stream config metadata.populate to true.

In addition to this, if you want to use any of these columns in your table, you have to list them explicitly in your table's schema.

For example, if you want to add only the offset and key as dimension columns in your Pinot table, it can listed in the schema as follows:

Once the schema is updated, these columns are similar to any other pinot column. You can apply ingestion transforms and / or define indexes on them.

Remember to follow the when updating schema of an existing table!

Tell Pinot where to find an Avro schema

There is a standalone utility to generate the schema from an Avro file. See [infer the pinot schema from the avro schema and JSON data]() for details.

To avoid errors like The Avro schema must be provided, designate the location of the schema in your streamConfigs section. For example, if your current section contains the following:

Then add this key: "stream.kafka.decoder.prop.schema"followed by a value that denotes the location of your schema.

Ingest streaming data from Apache Kafka

hashtagInstall and Launch Kafka

hashtagData Source

hashtagIngesting Data into Kafka

hashtagSchema

hashtagTable Config

hashtagCreate schema and table

hashtagQuerying

hashtagKafka ingestion guidelines

hashtagKafka versions in Pinot

hashtagUpgrade from Kafka 0.9 connector to Kafka 2.x connector

hashtagHow to consume from a Kafka version > 2.0.0

hashtagKafka configurations in Pinot

hashtagUse Kafka partition (low) level consumer with SSL

hashtagConsume transactionally-committed messages

hashtagUse Kafka partition (low) level consumer with SASL_SSL

hashtagExtract record headers as Pinot table columns

hashtagTell Pinot where to find an Avro schema

Ingest streaming data from Apache Kafka

hashtagInstall and Launch Kafka

hashtagData Source

hashtagIngesting Data into Kafka

hashtagSchema

hashtagTable Config

hashtagCreate schema and table

hashtagQuerying

hashtagKafka ingestion guidelines

hashtagKafka versions in Pinot

hashtagUpgrade from Kafka 0.9 connector to Kafka 2.x connector

hashtagHow to consume from a Kafka version > 2.0.0

hashtagKafka configurations in Pinot

hashtagUse Kafka partition (low) level consumer with SSL

hashtagConsume transactionally-committed messages

hashtagUse Kafka partition (low) level consumer with SASL_SSL

hashtagExtract record headers as Pinot table columns

hashtagTell Pinot where to find an Avro schema

Install and Launch Kafka

Data Source

Ingesting Data into Kafka

Schema

Table Config

Create schema and table

Querying

Kafka ingestion guidelines

Kafka versions in Pinot

Upgrade from Kafka 0.9 connector to Kafka 2.x connector

How to consume from a Kafka version > 2.0.0

Kafka configurations in Pinot

Use Kafka partition (low) level consumer with SSL

Consume transactionally-committed messages

Use Kafka partition (low) level consumer with SASL_SSL

Extract record headers as Pinot table columns

Tell Pinot where to find an Avro schema

Install and Launch Kafka

Data Source

Ingesting Data into Kafka

Schema

Table Config

Create schema and table

Querying

Kafka ingestion guidelines

Kafka versions in Pinot

Upgrade from Kafka 0.9 connector to Kafka 2.x connector

How to consume from a Kafka version > 2.0.0

Kafka configurations in Pinot

Use Kafka partition (low) level consumer with SSL

Consume transactionally-committed messages

Use Kafka partition (low) level consumer with SASL_SSL

Extract record headers as Pinot table columns

Tell Pinot where to find an Avro schema