Advanced Pinot Setup
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Set up Pinot by starting each component individually
Start Pinot Components using docker
Prerequisites
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
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.
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
Below are some configurations you can set in Pinot Controller. You can head over to Controller for complete list of available configs.
controller.helix.cluster.name
Pinot Cluster name
PinotCluster
controller.host
Pinot Controller Host
Required if config pinot.set.instance.id.to.hostname is false.
pinot.set.instance.id.to.hostname
When enabled, use server hostname to infer controller.host
false
controller.port
Pinot Controller Port
9000
controller.vip.host
The VIP hostname used to set the download URL for segments
${controller.host}
controller.vip.port
The VIP port used to set the download URL for segments
${controller.port}
controller.data.dir
Directory to host segment data
${java.io.tmpdir}/PinotController
controller.zk.str
Zookeeper URL
localhost:2181
cluster.tenant.isolation.enable
Enable Tenant Isolation, default is single tenant cluster
true
Below is a sample pinot-broker.conf
used in HelmChart setup.
pinot.broker.client.queryPort=8099
pinot.broker.routing.table.builder.class=random
pinot.set.instance.id.to.hostname=true
In order to run Pinot Broker, the command is:
bin/pinot-admin.sh StartBroker -clusterName pinot-quickstart -zkAddress pinot-zookeeper:2181 -configFileName config/pinot-broker.conf
Below are some configurations you can set in Pinot Broker. You can head over to Broker for complete list of available configs.
instanceId
Unique id to register Pinot Broker in the cluster.
BROKER_${BROKER_HOST}_${pinot.broker.client.queryPort}
pinot.set.instance.id.to.hostname
When enabled, use server hostname to set ${BROKER_HOST} in above config, else use IP address.
false
pinot.broker.client.queryPort
Port to query Pinot Broker
8099
pinot.broker.timeoutMs
Timeout for Broker Query in Milliseconds
10000
pinot.broker.enable.query.limit.override
Configuration to enable Query LIMIT Override to protect Pinot Broker and Server from fetch too many records back.
false
pinot.broker.query.response.limit
When config pinot.broker.enable.query.limit.override is enabled, reset limit for selection query if it exceeds this value.
2147483647
pinot.broker.startup.minResourcePercent
Configuration to consider the broker ServiceStatus as being STARTED if the percent of resources (tables) that are ONLINE for this this broker has crossed the threshold percentage of the total number of tables that it is expected to serve
100.0
Below is a sample pinot-server.conf
used in HelmChart setup.
pinot.server.netty.port=8098
pinot.server.adminapi.port=8097
pinot.server.instance.dataDir=/var/pinot/server/data/index
pinot.server.instance.segmentTarDir=/var/pinot/server/data/segment
pinot.set.instance.id.to.hostname=true
In order to run Pinot Server, the command is:
bin/pinot-admin.sh StartServer -clusterName pinot-quickstart -zkAddress pinot-zookeeper:2181 -configFileName config/pinot-server.conf
Below are some outstanding configurations you can set in Pinot Server. You can head over to Server for complete list of available configs.
instanceId
Unique id to register Pinot Server in the cluster.
Server_${SERVER_HOST}_${pinot.server.netty.port}
pinot.set.instance.id.to.hostname
When enabled, use server hostname to set ${SERVER_HOST} in above config, else use IP address.
false
pinot.server.netty.port
Port to query Pinot Server
8098
pinot.server.adminapi.port
Port for Pinot Server Admin UI
8097
pinot.server.instance.dataDir
Directory to hold all the data
${java.io.tmpDir}/PinotServer/index
pinot.server.instance.segmentTarDir
Directory to hold temporary segments downloaded from Controller or Deep Store
${java.io.tmpDir}/PinotServer/segmentTar
pinot.server.query.executor.timeout
Timeout for Server to process Query in Milliseconds
15000
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.
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"}
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.
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"}
sortedColumn
with streaming tablesFor 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.
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.
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.
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