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
When enabled, use server hostname to set ${BROKER_HOST} in above config, else use IP address.
false
pinot.broker.client.queryPort
Port to query Pinot Broker
8099
pinot.broker.timeoutMs
Timeout for Broker Query in Milliseconds
10000
pinot.broker.enable.query.limit.override
Configuration to enable Query LIMIT Override to protect Pinot Broker and Server from fetch too many records back.
false
pinot.broker.query.response.limit
When config pinot.broker.enable.query.limit.override is enabled, reset limit for selection query if it exceeds this value.
2147483647
pinot.broker.startup.minResourcePercent
Configuration to consider the broker ServiceStatus as being STARTED if the percent of resources (tables) that are ONLINE for this this broker has crossed the threshold percentage of the total number of tables that it is expected to serve
100.0
Pinot Server
Below is a sample pinot-server.conf used in HelmChart setup.
Below are some outstanding configurations you can set in Pinot Server. You can head over to Server for complete list of available configs.
Config Name
Description
Default Value
instanceId
Unique id to register Pinot Server in the cluster.
Server_${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
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.
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.
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.
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