All pages
Powered by GitBook
1 of 5

Loading...

Loading...

Loading...

Loading...

Loading...

External Clients

A lot of times the user wants to query data from an external application instead of using the built-in query explorer. Pinot provides external query client for this purpose. All of the clients have pretty standard interfaces so that the learning curve is minimum.

Currently Pinot provides the following clients

JDBCJavaPythonGolang

JDBC

Pinot offers standard JDBC interface to query the database. This makes it easier to integrate Pinot with other applications such as Tableau.

Installation

You can include the JDBC dependency in your code as follows -

You can also compile the into a JAR and place the JAR in the Drivers directory of your application.

There is no need to register the driver manually as it will automatically register itself at the startup of the application.

Usage

Here's an example of how to use the pinot-jdbc-client for querying. The client only requires the controller URL.

You can also use PreparedStatements. The placeholder parameters are represented using ? ** (question mark) symbol.

Authentication

Pinot supports , which can be enabled for your cluster using configuration. To support basic HTTP authorization in your client-side JDBC applications, make sure you are using Pinot JDBC 0.10.0+ or building from the latest Pinot snapshot. The following code snippet shows you how to connect to and query a Pinot cluster that has basic HTTP authorization enabled when using the JDBC client.

Configuring client time-out

The following timeouts can be set:

  • brokerConnectTimeoutMs (default 2000)

  • brokerReadTimeoutMs (default 60000)

  • brokerHandshakeTimeoutMs (default 2000)

  • controllerConnectTimeoutMs (default 2000)

  • controllerReadTimeoutMs (default 60000)

  • controllerHandshakeTimeoutMs (default 2000)

Timeouts for the JDBC connector can be added as a parameter to the JDBC Connection URL. The following example enables https and configures a very low timeout of 10ms:

Configuring client time-out

The following timeouts can be set:

  • brokerConnectTimeoutMs (default 2000)

  • brokerReadTimeoutMs (default 60000)

  • brokerHandshakeTimeoutMs (default 2000)

  • controllerConnectTimeoutMs (default 2000)

  • controllerReadTimeoutMs (default 60000)

  • controllerHandshakeTimeoutMs (default 2000)

Timeouts for the JDBC connector can be added as a parameter to the JDBC Connection URL. The following example enables https and configures a very low timeout of 10ms:

Limitation

The JDBC client doesn't support INSERT, DELETE or UPDATE statements due to the database limitations. You can only use the client to query the database. The driver is also not completely ANSI SQL 92 compliant.

If you want to use JDBC driver to integrate Pinot with other applications, do make sure to check JDBC ConnectionMetadata in your code. This will help in determining which features cannot be supported by Pinot since it is an OLAP database.

public static final String DB_URL = "jdbc:pinot://localhost:9000"
DriverManager.registerDriver(new PinotDriver());
Connection conn = DriverManager.getConnection(DB_URL);
Statement statement = conn.createStatement();
Integer limitResults = 10;
ResultSet rs = statement.executeQuery(String.format("SELECT UPPER(playerName) AS name FROM baseballStats LIMIT %d", limitResults));
Set<String> results = new HashSet<>();

while(rs.next()){
 String playerName = rs.getString("name");
 results.add(playerName);
}

conn.close();
Connection conn = DriverManager.getConnection(DB_URL);
PreparedStatement statement = conn.prepareStatement("SELECT UPPER(playerName) AS name FROM baseballStats WHERE age = ?");
statement.setInt(1, 20);

ResultSet rs = statement.executeQuery();
Set<String> results = new HashSet<>();

while(rs.next()){
 String playerName = rs.getString("name");
 results.add(playerName);
}

conn.close();
final String username = "admin";
final String password = "verysecret";

// Concatenate username and password and use base64 to encode the concatenated string
String plainCredentials = username + ":" + password;
String base64Credentials = new String(Base64.getEncoder().encode(plainCredentials.getBytes()));

// Create authorization header
String authorizationHeader = "Basic " + base64Credentials;
Properties connectionProperties = new Properties();
connectionProperties.setProperty("headers.Authorization", authorizationHeader);

// Register new Pinot JDBC driver
DriverManager.registerDriver(new PinotDriver());

// Get a client connection and set the encoded authorization header
Connection connection = DriverManager.getConnection(DB_URL, connectionProperties);

// Test that your query successfully authenticates
Statement statement = connection.createStatement();
ResultSet rs = statement.executeQuery("SELECT count(*) FROM baseballStats LIMIT 1;");

while (rs.next()) {
    String result = rs.getString("count(*)");
    System.out.println(result);
}
final String DB_URL = "jdbc:pinot://hostname?brokerConnectTimeoutMs=10&brokerReadTimeoutMs=10&brokerHandshakeTimeoutMs=10&controllerConnectTimeoutMs=10&controllerReadTimeoutMs=10&scheme=https";
JDBC code
basic HTTP authorization
<dependency>
    <groupId>org.apache.pinot</groupId>
    <artifactId>pinot-jdbc-client</artifactId>
    <version>0.8.0</version>
</dependency>
include 'org.apache.pinot:pinot-jdbc-client:0.8.0'

Golang

Pinot Client for Golang

Pinot provides a native Go client to query the database directly from Go application.

Install

  1. Follow this Pinot quickstart link to install and start Pinot locally.

bin/quick-start-batch.sh
  1. Check out the client library GitHub repository.

git clone [email protected]:startreedata/pinot-client-go.git
cd pinot-client-go
  1. Build and run the example application to query from the Pinot batch quickstart.

go build ./examples/batch-quickstart
./batch-quickstart

Use the Golang client

Create a Pinot connection

Initialize the Pinot client using one of the methods below.

Zookeeper Path

pinotClient := pinot.NewFromZookeeper([]string{"localhost:2123"}, "", "QuickStartCluster")

List of broker addresses

pinotClient := pinot.NewFromBrokerList([]string{"localhost:8000"})

ClientConfig

The Go client repository contains an example script.

Note: You need not configure “content-type” as a header in ExtraHTTPHeader.

pinotClient := pinot.NewWithConfig(&pinot.ClientConfig{
	ZkConfig: &pinot.ZookeeperConfig{
		ZookeeperPath:     zkPath,
		PathPrefix:        strings.Join([]string{zkPathPrefix, pinotCluster}, "/"),
		SessionTimeoutSec: defaultZkSessionTimeoutSec,
	},
    ExtraHTTPHeader: map[string]string{
        "extra-header": "value",
    },
})

ClientConfig with HTTP client

If you require a specialized HTTP client, you have the option to create your own HTTP client and utilize the NewWithConfigAndClient function to establish a Pinot client that can accommodate a custom HTTP client.

The Go client repository contains an example script.

Query Pinot

The Go client repository contains an example script.

Code snippet:

pinotClient, err := pinot.NewFromZookeeper([]string{"localhost:2123"}, "", "QuickStartCluster")
if err != nil {
    log.Error(err)
}
brokerResp, err := pinotClient.ExecuteSQL("baseballStats", "select count(*) as cnt, sum(homeRuns) as sum_homeRuns from baseballStats group by teamID limit 10")
if err != nil {
    log.Error(err)
}
log.Infof("Query Stats: response time - %d ms, scanned docs - %d, total docs - %d", brokerResp.TimeUsedMs, brokerResp.NumDocsScanned, brokerResp.TotalDocs)

Response format

The query response has the following format:

type BrokerResponse struct {
	AggregationResults          []*AggregationResult `json:"aggregationResults,omitempty"`
	SelectionResults            *SelectionResults    `json:"SelectionResults,omitempty"`
	ResultTable                 *ResultTable         `json:"resultTable,omitempty"`
	Exceptions                  []Exception          `json:"exceptions"`
	TraceInfo                   map[string]string    `json:"traceInfo,omitempty"`
	NumServersQueried           int                  `json:"numServersQueried"`
	NumServersResponded         int                  `json:"numServersResponded"`
	NumSegmentsQueried          int                  `json:"numSegmentsQueried"`
	NumSegmentsProcessed        int                  `json:"numSegmentsProcessed"`
	NumSegmentsMatched          int                  `json:"numSegmentsMatched"`
	NumConsumingSegmentsQueried int                  `json:"numConsumingSegmentsQueried"`
	NumDocsScanned              int64                `json:"numDocsScanned"`
	NumEntriesScannedInFilter   int64                `json:"numEntriesScannedInFilter"`
	NumEntriesScannedPostFilter int64                `json:"numEntriesScannedPostFilter"`
	NumGroupsLimitReached       bool                 `json:"numGroupsLimitReached"`
	TotalDocs                   int64                `json:"totalDocs"`
	TimeUsedMs                  int                  `json:"timeUsedMs"`
	MinConsumingFreshnessTimeMs int64                `json:"minConsumingFreshnessTimeMs"`
}

Note that AggregationResults and SelectionResults are holders for Pinot query language (PQL) queries.

Meanwhile, ResultTable is the holder for SQL queries. ResultTable is defined as:

// ResultTable is a ResultTable
type ResultTable struct {
	DataSchema RespSchema      `json:"dataSchema"`
	Rows       [][]interface{} `json:"rows"`
}

RespSchema is defined as:

// RespSchema is response schema
type RespSchema struct {
	ColumnDataTypes []string `json:"columnDataTypes"`
	ColumnNames     []string `json:"columnNames"`
}

There are multiple functions defined for ResultTable, such as the following:

func (r ResultTable) GetRowCount() int
func (r ResultTable) GetColumnCount() int
func (r ResultTable) GetColumnName(columnIndex int) string
func (r ResultTable) GetColumnDataType(columnIndex int) string
func (r ResultTable) Get(rowIndex int, columnIndex int) interface{}
func (r ResultTable) GetString(rowIndex int, columnIndex int) string
func (r ResultTable) GetInt(rowIndex int, columnIndex int) int
func (r ResultTable) GetLong(rowIndex int, columnIndex int) int64
func (r ResultTable) GetFloat(rowIndex int, columnIndex int) float32
func (r ResultTable) GetDouble(rowIndex int, columnIndex int) float64

See an example of a function in use here and below:

// Print Response Schema
for c := 0; c < brokerResp.ResultTable.GetColumnCount(); c++ {
  fmt.Printf("%s(%s)\t", brokerResp.ResultTable.GetColumnName(c), brokerResp.ResultTable.GetColumnDataType(c))
}
fmt.Println()

// Print Row Table
for r := 0; r < brokerResp.ResultTable.GetRowCount(); r++ {
  for c := 0; c < brokerResp.ResultTable.GetColumnCount(); c++ {
    fmt.Printf("%v\t", brokerResp.ResultTable.Get(r, c))
  }
  fmt.Println()
}

Java

Pinot provides a native java client to execute queries on the cluster. The client makes it easier for user to query data. The client is also tenant-aware and thus is able to redirect the queries to the correct broker.

Installation

You can use the client by including the following dependency -

<dependency>
    <groupId>org.apache.pinot</groupId>
    <artifactId>pinot-java-client</artifactId>
    <version>0.9.3</version>
</dependency>
include 'org.apache.pinot:pinot-java-client:0.5.0'

You can also build the code for java client locally and use it.

Basic authorization for the JDBC client is not supported in Pinot JDBC 0.9.3 release or earlier. The JDBC client has been upgraded to support basic authentication in the Pinot 0.10.0 snapshot, which can currently be built from source.

You will not need to update your Pinot cluster to 0.10.0+ to support basic authentication, only the JDBC and Java client JARs.

Usage

Here's an example of how to use the pinot-java-client to query Pinot.

import org.apache.pinot.client.Connection;
import org.apache.pinot.client.ConnectionFactory;
import org.apache.pinot.client.Request;
import org.apache.pinot.client.ResultSetGroup;
import org.apache.pinot.client.ResultSet;

/**
 * Demonstrates the use of the pinot-client to query Pinot from Java
 */
public class PinotClientExample {

  public static void main(String[] args) {

    // pinot connection
    String zkUrl = "localhost:2181";
    String pinotClusterName = "PinotCluster";
    Connection pinotConnection = ConnectionFactory.fromZookeeper(zkUrl + "/" + pinotClusterName);

    String query = "SELECT COUNT(*) FROM myTable GROUP BY foo";

    // set queryType=sql for querying the sql endpoint
    Request pinotClientRequest = new Request("sql", query);
    ResultSetGroup pinotResultSetGroup = pinotConnection.execute(pinotClientRequest);
    ResultSet resultTableResultSet = pinotResultSetGroup.getResultSet(0);

    int numRows = resultTableResultSet.getRowCount();
    int numColumns = resultTableResultSet.getColumnCount();
    String columnValue = resultTableResultSet.getString(0, 1);
    String columnName = resultTableResultSet.getColumnName(1);

    System.out.println("ColumnName: " + columnName + ", ColumnValue: " + columnValue);
  }
}

Connection Factory

The client provides a ConnectionFactory class to create connections to a Pinot cluster. The factory supports the following methods to create a connection -

  • Zookeeper (Recommended) - Comma-separated list of zookeeper of the cluster. This is the recommended method which can redirect queries to appropriate brokers based on tenant/table.

  • Broker list - Comma separated list of the brokers in the cluster. This should only be used in standalone setups or for POC, unless you have a load balancer setup for brokers.

  • Controller URL - (v 0.11.0+) Controller URL. This will use periodic controller API calls to keep the table level broker list updated (hence there might be delay b/w the broker mapping changing and the client state getting updated).

  • Properties file - You can also put the broker list as brokerList in a properties file and provide the path to that file to the factory. This should only be used in standalone setups or for POC, unless you have a load balancer setup for brokers.

If your Pinot cluster is running inside Kubernetes and you're trying to connect to it from outside Kubernetes, the Zookeeper method will probably return internal host names that can't be resolved. For Kubernetes deployments, it's therefore recommended to pass in the host-name of a load balancer sitting in front of the brokers.

Here's an example demonstrating all methods of Connection factory -

Connection connection = ConnectionFactory.fromZookeeper
  ("some-zookeeper-server:2191/zookeeperPath");

Connection connection = ConnectionFactory.fromProperties("demo.properties");

Connection connection = ConnectionFactory.fromHostList
  ("broker-1:1234", "broker-2:1234", ...);

Connection connection = ConnectionFactory.fromController
    ("http", "controller-url", 9000)

Query Methods

You can run the query in both blocking as well as async manner. Use

  • Connection.execute(org.apache.pinot.client.Request) for blocking queries

  • Connection.executeAsync(org.apache.pinot.client.Request) for asynchronous queries that return a future object.

ResultSetGroup resultSetGroup = 
  connection.execute(new Request("sql", "select * from foo..."));
// OR
Future<ResultSetGroup> futureResultSetGroup = 
  connection.executeAsync(new Request("sql", "select * from foo..."));

You can also use PreparedStatement to escape query parameters. We don't store the Prepared Statement in the database and hence it won't increase the subsequent query performance.

PreparedStatement statement = 
    connection.prepareStatement(new Request("sql", "select * from foo where a = ?"));
statement.setString(1, "bar");

ResultSetGroup resultSetGroup = statement.execute();
// OR
Future<ResultSetGroup> futureResultSetGroup = statement.executeAsync();

Result Set

Results can be obtained with the various get methods in the first ResultSet, obtained through the getResultSet(int) method:

Request request = new Request("sql", "select foo, bar from baz where quux = 'quuux'");
ResultSetGroup resultSetGroup = connection.execute(request);
ResultSet resultTableResultSet = pinotResultSetGroup.getResultSet(0);

for (int i = 0; i < resultSet.getRowCount(); ++i) {
  System.out.println("foo: " + resultSet.getString(i, 0));
  System.out.println("bar: " + resultSet.getInt(i, 1));
}

PQL Queries

If queryFormat pql is used in the Request, there are some differences in how the results can be accessed, depending on the query.

In the case of aggregation, each aggregation function is within its own ResultSet. A query with multiple aggregation function will return one result set per aggregation function, as they are computed in parallel.

ResultSetGroup resultSetGroup = 
    connection.execute(new Request("pql", "select max(foo), min(foo) from bar"));

System.out.println("Number of result groups:" +
    resultSetGroup.getResultSetCount(); // 2, min(foo) and max(foo)
ResultSet resultSetMax = resultSetGroup.getResultSet(0);
System.out.println("Max foo: " + resultSetMax.getInt(0));
ResultSet resultSetMin = resultSetGroup.getResultSet(1);
System.out.println("Min foo: " + resultSetMin.getInt(0));

In case of aggregation with GROUP BY, there will be as many ResultSets as the number of aggregations, each of which will contain multiple results grouped by a grouping key.

ResultSetGroup resultSetGroup = 
    connection.execute(
        new Request("pql", "select min(foo), max(foo) from bar group by baz"));

System.out.println("Number of result groups:" +
    resultSetGroup.getResultSetCount(); // 2, min(foo) and max(foo)

ResultSet minResultSet = resultSetGroup.getResultSet(0);
for(int i = 0; i < minResultSet.length(); ++i) {
    System.out.println("Minimum foo for " + minResultSet.getGroupKeyString(i, 1) +
        ": " + minResultSet.getInt(i));
}

ResultSet maxResultSet = resultSetGroup.getResultSet(1);
for(int i = 0; i < maxResultSet.length(); ++i) {
    System.out.println("Maximum foo for " + maxResultSet.getGroupKeyString(i, 1) +
        ": " + maxResultSet.getInt(i));
}

This section is only applicable for PQL endpoint, which is deprecated and will be deleted soon. For more information about the endpoints, visit Querying Pinot.

Authentication

Pinot supports basic HTTP authorization, which can be enabled for your cluster using configuration. To support basic HTTP authorization in your client-side Java applications, make sure you are using Pinot Java Client 0.10.0+ or building from the latest Pinot snapshot. The following code snippet shows you how to connect to and query a Pinot cluster that has basic HTTP authorization enabled when using the Java client.

final String username = "admin";
final String password = "verysecret";

// Concatenate username and password and use base64 to encode the concatenated string
String plainCredentials = username + ":" + password;
String base64Credentials = new String(
    Base64.getEncoder().encode(plainCredentials.getBytes()));

String authorizationHeader = "Basic " + base64Credentials;

Map<String, String> headers = new HashMap();
headers.put("Authorization", authorizationHeader);
JsonAsyncHttpPinotClientTransportFactory factory = 
    new JsonAsyncHttpPinotClientTransportFactory();
factory.setHeaders(headers);
PinotClientTransport clientTransport = factory
    .buildTransport();

Connection connection = ConnectionFactory.fromProperties(
        Collections.singletonList("localhost:8000"), clientTransport);
String query = "select count(*) FROM baseballStats limit 1";

ResultSetGroup rs = connection.execute(query);
System.out.println(rs);
connection.close();

Configuring client time-out

The following timeouts can be set:

  • brokerConnectTimeoutMs (default 2000)

  • brokerReadTimeoutMs (default 60000)

  • brokerHandshakeTimeoutMs (default 2000)

  • controllerConnectTimeoutMs (default 2000)

  • controllerReadTimeoutMs (default 60000)

  • controllerHandshakeTimeoutMs (default 2000)

Timeouts for the Java connector can be added as a connection properties. The following example configures a very low timeout of 10ms:

Properties connectionProperties = new Properties();
connectionProperties.setProperty("controllerReadTimeoutMs", "10");
connectionProperties.setProperty("controllerHandshakeTimeoutMs", "10");
connectionProperties.setProperty("controllerConnectTimeoutMs", "10");
connectionProperties.setProperty("brokerReadTimeoutMs", "10");
connectionProperties.setProperty("brokerHandshakeTimeoutMs", "10");
connectionProperties.setProperty("brokerConnectTimeoutMs", "10");

// Register new Pinot JDBC driver
DriverManager.registerDriver(new PinotDriver());

// Get a client connection and set the connection timeouts
Connection connection = DriverManager.getConnection(DB_URL, connectionProperties);

// Test that your query successfully times out
Statement statement = connection.createStatement();
ResultSet rs = statement.executeQuery("SELECT count(*) FROM baseballStats LIMIT 1;");

while (rs.next()) {
    String result = rs.getString("count(*)");
    System.out.println(result);
}

Python

Python DB-API and SQLAlchemy dialect for Pinot

Applications can use this python client library to query Apache Pinot.

Pypi Repo: https://pypi.org/project/pinotdb/

Source Code Repo: https://github.com/python-pinot-dbapi/pinot-dbapi

Installation

pip install pinotdb

Note:

  • pinotdb version >= 0.3.2 uses the Pinot SQL API (added in Pinot >= 0.3.0) and drops support for PQL API. So this client requires Pinot server version >= 0.3.0 in order to access Pinot.

  • pinotdb version in 0.2.x uses the Pinot PQL API, which works with pinot version <= 0.3.0, but may miss some new SQL query features added in newer Pinot version.

Usage

Using the DB API to query Pinot Broker directly:

from pinotdb import connect

conn = connect(host='localhost', port=8099, path='/query/sql', scheme='http')
curs = conn.cursor()
curs.execute("""
    SELECT place,
           CAST(REGEXP_EXTRACT(place, '(.*),', 1) AS FLOAT) AS lat,
           CAST(REGEXP_EXTRACT(place, ',(.*)', 1) AS FLOAT) AS lon
      FROM places
     LIMIT 10
""")
for row in curs:
    print(row)

Using SQLAlchemy:

The db engine connection string is formated like this: pinot://:?controller=://:/

from sqlalchemy import *
from sqlalchemy.engine import create_engine
from sqlalchemy.schema import *

engine = create_engine('pinot://localhost:8099/query/sql?controller=http://localhost:9000/')  # uses HTTP by default :(
# engine = create_engine('pinot+http://localhost:8099/query/sql?controller=http://localhost:9000/')
# engine = create_engine('pinot+https://localhost:8099/query/sql?controller=http://localhost:9000/')

places = Table('places', MetaData(bind=engine), autoload=True)
print(select([func.count('*')], from_obj=places).scalar())

Examples with Pinot Quickstart

Clone the Pinot DB repository

git clone [email protected]:python-pinot-dbapi/pinot-dbapi.git
cd pinot-dbapi

Pinot Batch Quickstart

Run below command to start Pinot Batch Quickstart in docker and expose Pinot controller port 9000 and Pinot broker port 8000.

docker run \
  --name pinot-quickstart \
  -p 2123:2123 \
  -p 9000:9000 \
  -p 8000:8000 \
  apachepinot/pinot:latest QuickStart -type batch

Once pinot batch quickstart is up, you can run the sample code snippet to query Pinot:

python3 examples/pinot-quickstart-batch.py

Sample Output:

Sending SQL to Pinot: SELECT * FROM baseballStats LIMIT 5
[0, 11, 0, 0, 0, 0, 0, 0, 0, 0, 'NL', 11, 11, 'aardsda01', 'David Allan', 1, 0, 0, 0, 0, 0, 0, 'SFN', 0, 2004]
[2, 45, 0, 0, 0, 0, 0, 0, 0, 0, 'NL', 45, 43, 'aardsda01', 'David Allan', 1, 0, 0, 0, 1, 0, 0, 'CHN', 0, 2006]
[0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 'AL', 25, 2, 'aardsda01', 'David Allan', 1, 0, 0, 0, 0, 0, 0, 'CHA', 0, 2007]
[1, 5, 0, 0, 0, 0, 0, 0, 0, 0, 'AL', 47, 5, 'aardsda01', 'David Allan', 1, 0, 0, 0, 0, 0, 1, 'BOS', 0, 2008]
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 'AL', 73, 3, 'aardsda01', 'David Allan', 1, 0, 0, 0, 0, 0, 0, 'SEA', 0, 2009]

Sending SQL to Pinot: SELECT playerName, sum(runs) FROM baseballStats WHERE yearID>=2000 GROUP BY playerName LIMIT 5
['Scott Michael', 26.0]
['Justin Morgan', 0.0]
['Jason Andre', 0.0]
['Jeffrey Ellis', 0.0]
['Maximiliano R.', 16.0]

Sending SQL to Pinot: SELECT playerName,sum(runs) AS sum_runs FROM baseballStats WHERE yearID>=2000 GROUP BY playerName ORDER BY sum_runs DESC LIMIT 5
['Adrian', 1820.0]
['Jose Antonio', 1692.0]
['Rafael', 1565.0]
['Brian Michael', 1500.0]
['Alexander Emmanuel', 1426.0]

Using parameters:

from pinotdb import connect

conn = connect(host='localhost', port=8000, path='/query/sql', scheme='http')
curs = conn.cursor()

curs.execute("""
    SELECT * 
    FROM baseballStats
    WHERE league IN (%(leagues)s)
    """, {"leagues": ["AA", "NL"]})
for row in curs:
    print(row)
    
curs.execute("""
    SELECT *
    FROM baseballStats
    WHERE baseOnBalls > (%(score)d)
    """, {"score": 0})
for row in curs:
    print(row)

Pinot Hybrid Quickstart

Run the command below to start Pinot Hybrid Quickstart in docker and expose Pinot controller port 9000 and Pinot broker port 8000.

docker run \
  --name pinot-quickstart \
  -p 2123:2123 \
  -p 9000:9000 \
  -p 8000:8000 \
  apachepinot/pinot:latest QuickStart -type hybrid

Below is an example to query against Pinot Quickstart Hybrid:

python3 examples/pinot-quickstart-hybrid.py
Sending SQL to Pinot: SELECT * FROM airlineStats LIMIT 5
[171, 153, 19393, 0, 8, 8, 1433, '1400-1459', 0, 1425, 1240, 165, 'null', 0, 'WN', -2147483648, 1, 27, 17540, 0, 2, 2, 1242, '1200-1259', 0, 'MDW', 13232, 1323202, 30977, 'Chicago, IL', 'IL', 17, 'Illinois', 41, 861, 4, -2147483648, [-2147483648], 0, [-2147483648], ['null'], -2147483648, -2147483648, [-2147483648], -2147483648, ['null'], [-2147483648], [-2147483648], [-2147483648], 0, -2147483648, '2014-01-27', 402, 1, -2147483648, -2147483648, 1, -2147483648, 'BOS', 10721, 1072102, 30721, 'Boston, MA', 'MA', 25, 'Massachusetts', 13, 1, ['null'], -2147483648, 'N556WN', 6, 12, -2147483648, 'WN', -2147483648, 1254, 1427, 2014]
[183, 141, 20398, 1, 17, 17, 1302, '1200-1259', 1, 1245, 1005, 160, 'null', 0, 'MQ', 0, 1, 27, 17540, 0, -6, 0, 959, '1000-1059', -1, 'CMH', 11066, 1106603, 31066, 'Columbus, OH', 'OH', 39, 'Ohio', 44, 990, 4, -2147483648, [-2147483648], 0, [-2147483648], ['null'], -2147483648, -2147483648, [-2147483648], -2147483648, ['null'], [-2147483648], [-2147483648], [-2147483648], 0, -2147483648, '2014-01-27', 3574, 1, 0, -2147483648, 1, 17, 'MIA', 13303, 1330303, 32467, 'Miami, FL', 'FL', 12, 'Florida', 33, 1, ['null'], 0, 'N605MQ', 13, 29, -2147483648, 'MQ', 0, 1028, 1249, 2014]
[-2147483648, -2147483648, 20304, -2147483648, -2147483648, -2147483648, -2147483648, '2100-2159', -2147483648, 2131, 2005, 146, 'null', 0, 'OO', -2147483648, 1, 27, 17541, 1, 52, 52, 2057, '2000-2059', 3, 'COS', 11109, 1110902, 30189, 'Colorado Springs, CO', 'CO', 8, 'Colorado', 82, 809, 4, -2147483648, [11292], 1, [1129202], ['DEN'], -2147483648, 73, [9], 0, ['null'], [9], [-2147483648], [2304], 1, -2147483648, '2014-01-27', 5554, 1, -2147483648, -2147483648, 1, -2147483648, 'IAH', 12266, 1226603, 31453, 'Houston, TX', 'TX', 48, 'Texas', 74, 1, ['SEA', 'PSC', 'PHX', 'MSY', 'ATL', 'TYS', 'DEN', 'CHS', 'PDX', 'LAX', 'EWR', 'SFO', 'PIT', 'RDU', 'RAP', 'LSE', 'SAN', 'SBN', 'IAH', 'OAK', 'BRO', 'JFK', 'SAT', 'ORD', 'ACY', 'DFW', 'BWI'], -2147483648, 'N795SK', -2147483648, 19, -2147483648, 'OO', -2147483648, 2116, -2147483648, 2014]
[153, 125, 20436, 1, 41, 41, 1442, '1400-1459', 2, 1401, 1035, 146, 'null', 0, 'F9', 2, 1, 27, 17541, 1, 34, 34, 1109, '1000-1059', 2, 'DEN', 11292, 1129202, 30325, 'Denver, CO', 'CO', 8, 'Colorado', 82, 967, 4, -2147483648, [-2147483648], 0, [-2147483648], ['null'], -2147483648, -2147483648, [-2147483648], -2147483648, ['null'], [-2147483648], [-2147483648], [-2147483648], 0, -2147483648, '2014-01-27', 658, 1, 8, -2147483648, 1, 31, 'SFO', 14771, 1477101, 32457, 'San Francisco, CA', 'CA', 6, 'California', 91, 1, ['null'], 0, 'N923FR', 11, 17, -2147483648, 'F9', 0, 1126, 1431, 2014]
[-2147483648, -2147483648, 20304, -2147483648, -2147483648, -2147483648, -2147483648, '1400-1459', -2147483648, 1432, 1314, 78, 'B', 1, 'OO', -2147483648, 1, 27, 17541, -2147483648, -2147483648, -2147483648, -2147483648, '1300-1359', -2147483648, 'EAU', 11471, 1147103, 31471, 'Eau Claire, WI', 'WI', 55, 'Wisconsin', 45, 268, 2, -2147483648, [-2147483648], 0, [-2147483648], ['null'], -2147483648, -2147483648, [-2147483648], -2147483648, ['null'], [-2147483648], [-2147483648], [-2147483648], 0, -2147483648, '2014-01-27', 5455, 1, -2147483648, -2147483648, 1, -2147483648, 'ORD', 13930, 1393003, 30977, 'Chicago, IL', 'IL', 17, 'Illinois', 41, 1, ['null'], -2147483648, 'N903SW', -2147483648, -2147483648, -2147483648, 'OO', -2147483648, -2147483648, -2147483648, 2014]

Sending SQL to Pinot: SELECT count(*) FROM airlineStats LIMIT 5
[17772]

Sending SQL to Pinot: SELECT AirlineID, sum(Cancelled) FROM airlineStats WHERE Year > 2010 GROUP BY AirlineID LIMIT 5
[20409, 40.0]
[19930, 16.0]
[19805, 60.0]
[19790, 115.0]
[20366, 172.0]

Sending SQL to Pinot: select OriginCityName, max(Flights) from airlineStats group by OriginCityName ORDER BY max(Flights) DESC LIMIT 5
['Casper, WY', 1.0]
['Deadhorse, AK', 1.0]
['Austin, TX', 1.0]
['Chicago, IL', 1.0]
['Monterey, CA', 1.0]

Sending SQL to Pinot: SELECT OriginCityName, sum(Cancelled) AS sum_cancelled FROM airlineStats WHERE Year>2010 GROUP BY OriginCityName ORDER BY sum_cancelled DESC LIMIT 5
['Chicago, IL', 178.0]
['Atlanta, GA', 111.0]
['New York, NY', 65.0]
['Houston, TX', 62.0]
['Denver, CO', 49.0]

Sending Count(*) SQL to Pinot
17773

Sending SQL: "SELECT OriginCityName, sum(Cancelled) AS sum_cancelled FROM "airlineStats" WHERE Year>2010 GROUP BY OriginCityName ORDER BY sum_cancelled DESC LIMIT 5" to Pinot
[('Chicago, IL', 178.0), ('Atlanta, GA', 111.0), ('New York, NY', 65.0), ('Houston, TX', 62.0), ('Denver, CO', 49.0)]