Can we join a table (offline/realtime) with two or more dimension(lookup) tables?

I know we can do a join with one lookup table, but I wonder if we can do with more than one?

Hi Team not able to append data into table .this is the table config i'm using ,is there any thing needs to be added here to support append mode ?

{
  "tableName": "rcem_map_dly2",
  "tableType": "OFFLINE",
  "segmentsConfig": {
    "segmentPushType": "APPEND",
    "segmentAssignmentStrategy": "BalanceNumSegmentAssignmentStrategy",
    "schemaName": "rcem_map_dly2",
    "replication": "1"
  },
  "tenants": {
    "broker": "DefaultTenant",
    "server": "DefaultTenant"
  },
  "tableIndexConfig": {
    "loadMode": "MMAP"
  },
  "ingestionConfig": {
    "batchIngestionConfig": {
      "segmentIngestionType": "APPEND",
      "segmentIngestionFrequency": "DAILY"
    }
  },
  "metadata": {}
}

Hi Team, I am trying to get the Unique Records count on 60M records (column : ID) I have created the Inverted iNdex on ID column .. Getting the following error

java.lang.OutOfMemoryError: Java heap space

how to increase the heap size ?

Hi team, I ran a batch ingestion spark job on AWS EMR cluster:

spark-submit --class org.apache.pinot.tools.admin.command.LaunchDataIngestionJobCommand --master yarn --jars "<s3://dataplatform/jars/pinot-batch-ingestion-spark-3.2-0.11.0-shaded.jar,s3://dataplatform/jars/pinot-all-0.11.0-jar-with-dependencies.jar>" --conf spark.driver.userClassPathFirst=true --conf spark.executor.userClassPathFirst=true --deploy-mode client --conf "spark.driver.extraClassPath=pinot-batch-ingestion-spark-3.2-0.11.0-shaded.jar:pinot-all-0.11.0-jar-with-dependencies.jar" --conf "spark.executor.extraClassPath=pinot-batch-ingestion-spark-3.2-0.11.0-shaded.jar:pinot-all-0.11.0-jar-with-dependencies.jar"  --files <s3://testbucket-data/test/spark_spec92.yaml> <local://pinot-all-0.11.0-jar-with-dependencies.jar> -jobSpecFile spark_spec92.yaml

can somebody please help with this error : Caused by: java.lang.ClassNotFoundException: org.apache.pinot.plugin.filesystem.S3PinotFS

Hi team, how does Pinot decide the

maxRowCount

of a segment in the following cases: 1.

realtime.segment.flush.threshold.rows

is not set in the stream config. 2.

realtime.segment.flush.threshold.rows

is set to

"0"

in the stream config. Here’s a log of a segment with flush time of

1h

and

realtime.segment.flush.threshold.rows

as 0:

2022/11/17 17:44:46.259 INFO [LLRealtimeSegmentDataManager_raw_service_view_1__9__477__20221117T1744Z] [HelixTaskExecutor-message_handle_thread_23] Starting consumption on realtime consuming segment raw_service_view_1__9__477__20221117T1744Z maxRowCount 703125 maxEndTime 2022-11-17T18:44:44.653Z

The max end-time is fine, but how is it getting the

maxRowCount

as 703125? I could not look for any such logic in code:

PartitionLevelStreamConfig#extractFlushThresholdRows

. Similarly, when

realtime.segment.flush.threshold.rows

is null, it again prints a random value. Want to understand how this is being calculated? My use-case is I want to flush the segment only based on endtime. That is, after every 1h. So I set only

"realtime.segment.flush.threshold.time": "1h"

and no other prop.

Hi folks. Could someone explain to me how retention is being handled? How does Pinot determine which segments to toss out?

We are trying to figure out the best pattern for filtering (mostly by date-related things, but could apply to other things) and we are seeing differences when filtering in the WHERE clause vs. the HAVING clause. The HAVING clause seems much faster. I'll add a sample query in a thread.

I want to batch ingest data stored in S3 into Pinot. The data is partitioned with two fields in the S3 path like this: s3://my-bucket/path/customer=abc/day=2022-11-15/*.snappy.parquet The day/date field and the customer field are in the S3 path, not in the Parquet files. Apache Spark reads/writes this correctly. So, using Apache Spark would be one way to get this data imported, but I would like to not use Spark if possible. I was hoping to use Pinot’s ingestion job system or something similar. Does Pinot’s data ingestion job support this? I’m looking at the ingestion jobspec docs, and I don’t see any configuration regarding this. Can it be done? Do I have any other options other than using Spark to load this data? Thank you 🙂

Hi Team, below pinot data attribute is considered as number by superset. How can external clients (like superset) treat it as timestamp ? { “name”: “MAX_TIME_CREATED”, “dataType”: “LONG”, “format”: “1MILLISECONDSEPOCH”, “granularity”: “1:SECONDS” }

Hi Team facing this issue while running spark data ingestion ,using spark 3+ and java 11 and pinot 0.11.0 versions . SLF4J: Found binding in [jarfile/home/mahesh/working_dir/spark-3.3.0-bin-hadoop3/jars/log4j-slf4j-impl-2.17.2.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory] 2022/11/18 134100.285 ERROR [LaunchDataIngestionJobCommand] [main] Got exception to kick off standalone data ingestion job - java.lang.RuntimeException: Failed to create IngestionJobRunner instance for class - org.apache.pinot.plugin.ingestion.batch.spark.SparkSegmentGenerationJobRunner *at org.apache.pinot.spi.ingestion.batch.IngestionJobLauncher.kickoffIngestionJob(IngestionJobLauncher.java:145) ~[pinot-all-0.11.0-jar-with-dependencies.jar:0.11.0-*1b4d6b6b0a27422c1552ea1a936ad145056f7033] at org.apache.pinot.spi.ingestion.batch.IngestionJobLauncher.runIngestionJob(IngestionJobLauncher.java:121) ~[pinot-all-0.11.0-jar-with-dependencies.jar:0.11.0-1b4d6b6b0a27422c1552ea1a936ad145056f7033] at org.apache.pinot.tools.admin.command.LaunchDataIngestionJobCommand.execute(LaunchDataIngestionJobCommand.java:130) [pinot-all-0.11.0-jar-with-dependencies.jar:0.11.0-1b4d6b6b0a27422c1552ea1a936ad145056f7033] at org.apache.pinot.tools.Command.call(Command.java:33) [pinot-all-0.11.0-jar-with-dependencies.jar:0.11.0-1b4d6b6b0a27422c1552ea1a936ad145056f7033] at org.apache.pinot.tools.Command.call(Command.java:29) [pinot-all-0.11.0-jar-with-dependencies.jar:0.11.0-1b4d6b6b0a27422c1552ea1a936ad145056f7033] at picocli.CommandLine.executeUserObject(CommandLine.java:1953) [pinot-all-0.11.0-jar-with-dependencies.jar:0.11.0-1b4d6b6b0a27422c1552ea1a936ad145056f7033]

Hi team. We increased zookeeper replicas but unfortunately facing errors in some of the tables after that. Zookeeper does not have metadata for some of the segments. Error:

Failed to find segment ZK metadata for segment:

, which is causing high consumer lag. Can someone suggest how can we fix this issue? Thanks Update: Searching for similar errors here on slack helped. https://apache-pinot.slack.com/archives/C011C9JHN7R/p1649665219641519 . Restarted all the components and pausing and restarting the consumption for all the tables helped in resolving the issue.

Hi, after upgrading to 0.11.0, I've noticed that our batch ingestion fails occasionally when using the pinot admin and SegmentCreationAndMetadataPush. During the segment push, it gets an exception. Afterwards, it seems to log that the segment has been successfully pushed. However, the segment is actually in a bad state and queries to the table will fail due to that segment. We usually have to delete and redo the ingestion to correct this. Any ideas for what causes this?

From https://docs.pinot.apache.org/v/release-0.11.0/basics/data-import/from-query-console, there is the following example:

INSERT INTO "baseballStats"
FROM FILE '<s3://my-bucket/public_data_set/baseballStats/rawdata/>'
OPTION(taskName=myTask-s3)
OPTION(input.fs.className=org.apache.pinot.plugin.filesystem.S3PinotFS)
OPTION(input.fs.prop.accessKey=my-key)
OPTION(input.fs.prop.secretKey=my-secret)
OPTION(input.fs.prop.region=us-west-2)

When I open up the pinot controller web interface, use the SQL/PQL Query console, paste that query in and run it, I get a parse exception:

ProcessingException(errorCode:150, message:PQLParsingError:
org.apache.pinot.sql.parsers.SqlCompilationException: Caught exception while parsing query: INSERT INTO "baseballStats"
FROM FILE '<s3://my-bucket/public_data_set/baseballStats/rawdata/>'
	at org.apache.pinot.sql.parsers.CalciteSqlParser.compileToPinotQuery(CalciteSqlParser.java:139)
	at org.apache.pinot.sql.parsers.CalciteSqlCompiler.compileToBrokerRequest(CalciteSqlCompiler.java:35)
	at org.apache.pinot.controller.api.resources.PinotQueryResource.getQueryResponse(PinotQueryResource.java:166)
...
Caused by: org.apache.calcite.sql.parser.SqlParseException: Incorrect syntax near the keyword 'FROM' at line 2, column 1.
Was expecting one of:
    "/*+" ...
    "(" ...
    "WITH" ...
...
Caused by: org.apache.calcite.sql.parser.babel.ParseException: Incorrect syntax near the keyword 'FROM' at line 2, column 1.
Was expecting one of:
    "/*+" ...
    "(" ...
    "WITH" ...)

So, the example in the official documentation should parse successfully. It should error because the table name + S3 location + access key are invalid, but I know how to fix that. I’d like to get the basic syntax of this command working first. Am I possibly running the wrong version of Pinot?

On a new Pinot 0.11.0 Kubernetes/Helm setup, if I use the built-in query console on the Pinot controller web interface run

select count(*) from my_table;

, I see the query response stats, but I don’t see the query results. Why? Pinot has a built-in SQL query engine based on Calcite and also integrates with Trino and Presto for SQL query capabilities. When would I want to use the built-in SQL vs Trino vs Presto?

The Pinot minion is core dumping when importing data. BTW, in my previous posts I had the Parquet date field configured wrong, that was erroring, and data wasn’t being imported. Now that that is fixed, I see the minion core dump. Here are abbreviated logs:

RecordReader initialized will read a total of 51031051 records.
<snip>
Finished building StatsCollector!
Collected stats for 51031051 documents
<snip>
Start building IndexCreator!
<snip>
Assembled and processed 40733690 records from 25 columns in 346811 ms: 117.452126 rec/ms, 2936.303 cell/ms
time spent so far 0% reading (496 ms) and 99% processing (346811 ms)
at row 40733690. reading next block
block read in memory in 92 ms. row count = 6683170
Assembled and processed 47416860 records from 25 columns in 403202 ms: 117.60075 rec/ms, 2940.0188 cell/ms
time spent so far 0% reading (588 ms) and 99% processing (403202 ms)
at row 47416860. reading next block
block read in memory in 35 ms. row count = 3614191
Finished records indexing in IndexCreator!
Finished segment seal!
Converting segment: /var/pinot/minion/data/SegmentGenerationAndPushResult/tmp-27d53515-e7c4-46a5-9655-75221c493a9e/output/oemdashboard_OFFLINE_17743_19312_0 to v3 format
Reflections took 181 ms to scan 2 urls, producing 16 keys and 35 values 
Initialized SegmentDirectoryLoaderRegistry with 1 segmentDirectoryLoaders: [default] in 185 ms
#
# A fatal error has been detected by the Java Runtime Environment:
#
#  SIGBUS (0x7) at pc=0x00007f0a8c85d166, pid=1, tid=62
#
# JRE version: OpenJDK Runtime Environment 18.9 (11.0.16+8) (build 11.0.16+8)
# Java VM: OpenJDK 64-Bit Server VM 18.9 (11.0.16+8, mixed mode, sharing, tiered, compressed oops, g1 gc, linux-amd64)
# Problematic frame:
# v  ~StubRoutines::jbyte_disjoint_arraycopy
#
# Core dump will be written. Default location: /opt/pinot/core.1
#
# An error report file with more information is saved as:
# /opt/pinot/hs_err_pid1.log
Compiled method (c2) 1390132 7053       4       jdk.internal.misc.Unsafe::copyMemory (33 bytes)
 total in heap  [0x00007f0a94769010,0x00007f0a94769848] = 2104
 relocation     [0x00007f0a94769188,0x00007f0a947691a8] = 32
 main code      [0x00007f0a947691c0,0x00007f0a947694e0] = 800
 stub code      [0x00007f0a947694e0,0x00007f0a947694f8] = 24
 metadata       [0x00007f0a947694f8,0x00007f0a94769538] = 64
 scopes data    [0x00007f0a94769538,0x00007f0a94769778] = 576
 scopes pcs     [0x00007f0a94769778,0x00007f0a94769828] = 176
 dependencies   [0x00007f0a94769828,0x00007f0a94769830] = 8
 nul chk table  [0x00007f0a94769830,0x00007f0a94769848] = 24
Compiled method (c2) 1390134 7053       4       jdk.internal.misc.Unsafe::copyMemory (33 bytes)
 total in heap  [0x00007f0a94769010,0x00007f0a94769848] = 2104
 relocation     [0x00007f0a94769188,0x00007f0a947691a8] = 32
 main code      [0x00007f0a947691c0,0x00007f0a947694e0] = 800
 stub code      [0x00007f0a947694e0,0x00007f0a947694f8] = 24
 metadata       [0x00007f0a947694f8,0x00007f0a94769538] = 64
 scopes data    [0x00007f0a94769538,0x00007f0a94769778] = 576
 scopes pcs     [0x00007f0a94769778,0x00007f0a94769828] = 176
 dependencies   [0x00007f0a94769828,0x00007f0a94769830] = 8
 nul chk table  [0x00007f0a94769830,0x00007f0a94769848] = 24
Could not load hsdis-amd64.so; library not loadable; PrintAssembly is disabled

Hi Team, just wanted to verify if i configured my star tree index correctly according to my query. I tried benchmarking this query performance between 2 similar tables, 1 with inverted index on cityID, vehicle ID and geohash and another table with those inverted indexes stated + star tree index shown below. However, the query performance did not improve and at times, it is worst. I ordered my dimensionsplitorder in the level or cardinality. Thanks for your help in advance 🙏 Query:

select AVG(value) as value from table where cityID = 6 AND vehicleID IN (302) and eventTime > cast(now()-86400000 as timestamp) group by geohash, eventTime limit 10000000

"starTreeIndexConfigs": [
        {
          "dimensionsSplitOrder": [
            "cityID",
            "vehicleID",
            "eventTime",
            "geohash"
          ],
          "skipStarNodeCreationForDimensions": [],
          "functionColumnPairs": [
            "AVG__value"
          ],
          "maxLeafRecords": 1000
        }
      ],
      "enableDynamicStarTreeCreation": true,

When installing Presto for use with a new Pinot 0.11.0 installation, which Docker image tag should I use with Docker repo

apachepinot/pinot-presto

? I’m currently using tag

pinot-0.11.0-preview

. I don’t see a non-preview 0.11.0 version. Almost all the recent image tags are snapshot tags.

Why would this query fail? If I run same query with minor syntax modifications in Presto against the same Pinot database, that works. It takes 15+ seconds, which is slower than I’d like, but it works with Presto. BTW, simpler queries work successfully in the Pinot web interface. And FYI, Pinot seems to be significantly faster for simple queries than Presto queries connected to the same Pinot database.

Is the v2 Multi-Stage Query Engine usable in v0.11.0? If so, I’d like to try it out. The docs say to “add the following configurations to your cluster config”:

"pinot.multistage.engine.enabled": "true",
"pinot.server.instance.currentDataTableVersion": "4",
"pinot.query.server.port": "8421",
"pinot.query.runner.port": "8442"

The Helm chart offers “controller.extra.configs”, “broker.extra.configs”, “server.extra.configs”, “minion.extra.configs”, “minionStateless.extra.configs”. Do I add the four specified config settings to one of these or to something else? For reference: Multi-Stage-Query-Engine Docs: https://docs.pinot.apache.org/developers/advanced/v2-multi-stage-query-engine#troubleshoot Helm Chart Values: https://github.com/apache/pinot/blob/master/kubernetes/helm/pinot/values.yaml

Hi, I am testing pinot client go library. I started Pinot in local and am able to get the data from table

baseballStats

in query console(as screenshot shows). However, when I follow this: https://github.com/startreedata/pinot-client-go and run ./batch-quickstart. I got the error:

$ ./batch-quickstart

2022/11/21 172407 Failed to connect to [:1]2123: dial tcp [:1]2123: connect: connection refused

2022/11/21 172407 Failed to connect to 127.0.0.12123 dial tcp 127.0.0.12123 connect: connection refused

ERRO[0000] Failed to set a watcher on ExternalView path: localhost:2123/QuickStartCluster/EXTERNALVIEW/brokerResource, Error: zk: could not connect to a server

INFO[0000] Querying SQL

INFO[0000] Trying to query Pinot: select * from baseballStats limit 10

ERRO[0000] Unable to find an available broker for table baseballStats, Error: Unable to find the table: baseballStats

ERRO[0000] Unable to find the table: baseballStats

panic: runtime error: invalid memory address or nil pointer dereference

[signal SIGSEGV: segmentation violation code=0x2 addr=0xa0 pc=0x1022e0200]

goroutine 1 [running]:

main.printBrokerResp(0x0)

/Users/xiaodong.zhou/Desktop/pinot_workspace/pinot-client-go/examples/batch-quickstart/main.go:38 +0x30

main.main()

/Users/xiaodong.zhou/Desktop/pinot_workspace/pinot-client-go/examples/batch-quickstart/main.go:33 +0x21c

Anyone knows why I can’t get the table baseballStats from pinot client go library? Thanks.

Hi, I setup a schema with a field from the Kafka record timestamp as follow

{
  "name": "__metadata$recordTimestamp",
  "dataType": "STRING"
}

However, all fields have the same value

-9223372036854775808

wich is not correct. Any ideas ?

Hello, I’m trying to retrieve some data from pinot with a simple query:

SELECT * FROM worker_datasource_637cf8beaaee000100312f92_637cf8beaaee631c90312f91_1
WHERE (("reference" = '4') OR ("reference" = '3') OR ("reference" = '1') OR ("reference" = '2'))
LIMIT 0,20

I would like to know if this is possible for Pinot to return results ordered based on filters order? Here I would like to have the row with reference=4 first, reference=3 second… Currently it sort rows based on the $docId Thank you

Hi team, I am trying to add a new schema using rest api. Provided schema :

{
  "schemaName": "lineitem_spark92",
  "dimensionFieldSpecs": [
    {
      "name": "l_orderkey",
      "dataType": "INT",
      "defaultNullValue": 0
    },
    {
      "name": "l_partkey",
      "dataType": "INT",
      "defaultNullValue": 0
    },
    {
      "name": "l_suppkey",
      "dataType": "INT",
      "defaultNullValue": 0
    },
    {
      "name": "l_linenumber",
      "dataType": "INT",
      "defaultNullValue": 0
    },
    {
      "name": "l_returnflag",
      "dataType": "STRING",
      "defaultNullValue": "null"
    },
    {
      "name": "l_linestatus",
      "dataType": "STRING",
      "defaultNullValue": "null"
    },
    {
      "name": "l_shipdate",
      "dataType": "STRING",
      "defaultNullValue": "null"
    },
    {
      "name": "l_commitdate",
      "dataType": "STRING",
      "defaultNullValue": "null"
    },
    {
      "name": "l_receiptdate",
      "dataType": "STRING",
      "defaultNullValue": "null"
    },
    {
      "name": "l_shipinstruct",
      "dataType": "STRING",
      "defaultNullValue": "null"
    },
    {
      "name": "l_shipmode",
      "dataType": "STRING",
      "defaultNullValue": "null"
    },
    {
      "name": "l_comment1",
      "dataType": "STRING",
      "defaultNullValue": "null"
    }
  ],
  "metricFieldSpecs": [
    {
      "name": "l_quantity",
      "dataType": "LONG",
      "defaultNullValue": 0
    },
    {
      "name": "l_extendedprice",
      "dataType": "DOUBLE",
      "defaultNullValue": 0
    },
    {
      "name": "l_discount",
      "dataType": "DOUBLE",
      "defaultNullValue": 0
    },
    {
      "name": "l_tax",
      "dataType": "DOUBLE",
      "defaultNullValue": 0
    }
  ]
}

Schema shown in pinot :

{
  "schemaName": "lineitem_spark92",
  "dimensionFieldSpecs": [
    {
      "name": "l_orderkey",
      "dataType": "INT",
      "defaultNullValue": 0
    },
    {
      "name": "l_partkey",
      "dataType": "INT",
      "defaultNullValue": 0
    },
    {
      "name": "l_suppkey",
      "dataType": "INT",
      "defaultNullValue": 0
    },
    {
      "name": "l_linenumber",
      "dataType": "INT",
      "defaultNullValue": 0
    },
    {
      "name": "l_returnflag",
      "dataType": "STRING"
    },
    {
      "name": "l_linestatus",
      "dataType": "STRING"
    },
    {
      "name": "l_shipdate",
      "dataType": "STRING"
    },
    {
      "name": "l_commitdate",
      "dataType": "STRING"
    },
    {
      "name": "l_receiptdate",
      "dataType": "STRING"
    },
    {
      "name": "l_shipinstruct",
      "dataType": "STRING"
    },
    {
      "name": "l_shipmode",
      "dataType": "STRING"
    },
    {
      "name": "l_comment1",
      "dataType": "STRING"
    }
  ],
  "metricFieldSpecs": [
    {
      "name": "l_quantity",
      "dataType": "LONG"
    },
    {
      "name": "l_extendedprice",
      "dataType": "DOUBLE"
    },
    {
      "name": "l_discount",
      "dataType": "DOUBLE"
    },
    {
      "name": "l_tax",
      "dataType": "DOUBLE"
    }
  ]
}

defaultNullValues are getting omitted for most of the fields. Am I doing something incorrect here? Also, my spark batch ingestion job is failing with :

Caused by: java.lang.NumberFormatException: For input string: "null"
	at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
	at java.lang.Long.parseLong(Long.java:589)
	at java.lang.Long.parseLong(Long.java:631)

can someone please help with this?

Can you try a different default value (say non zero for metrics), just for testing?

For the error above, it seems you have defined something as int/long, but the input contains a “null” string

Hi, does anyone know how to view the queries being executed on brokers and servers?

Hi all, I was modifying my kafka installation for my realtime table but it doesn’t seem like the realtime ingestion is resuming but I see this in the logs for the server, is this an error?

👋 hi folks, Trying to pin point an issue we are seeing with

RetentionManger

where our segments are not being removed as expected - we are running pinot 0.11.0. I will share the table config and controller config in thread 🧵

hi folks, i was trying to test the pinot-flink-connector at pinot/pinot-connectors/pinot-flink-connector when submitting the jar though i see the exception below. Any idea whats going on? nkshah@docdbpogo1:~/Flinkexamples/flink-api-examples$ ./flink-1.16.0/bin/flink run -c org.apache.pinot.connector.flink.FlinkQuickStart ~/pinot/pinot-connectors/pinot-flink-connector/target/pinot-flink-connector-0.12.0-SNAPSHOT.jar java.lang.NoClassDefFoundError: org/apache/pinot/common/utils/http/HttpClient at org.apache.pinot.connector.flink.FlinkQuickStart.main(FlinkQuickStart.java:85) at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.base/java.lang.reflect.Method.invoke(Method.java:566) at org.apache.flink.client.program.PackagedProgram.callMainMethod(PackagedProgram.java:355) at org.apache.flink.client.program.PackagedProgram.invokeInteractiveModeForExecution(PackagedProgram.java:222) at org.apache.flink.client.ClientUtils.executeProgram(ClientUtils.java:98) at org.apache.flink.client.cli.CliFrontend.executeProgram(CliFrontend.java:846) at org.apache.flink.client.cli.CliFrontend.run(CliFrontend.java:240) at org.apache.flink.client.cli.CliFrontend.parseAndRun(CliFrontend.java:1090) at org.apache.flink.client.cli.CliFrontend.lambda$main$10(CliFrontend.java:1168) at org.apache.flink.runtime.security.contexts.NoOpSecurityContext.runSecured(NoOpSecurityContext.java:28) at org.apache.flink.client.cli.CliFrontend.main(CliFrontend.java:1168) Caused by: java.lang.ClassNotFoundException: org.apache.pinot.common.utils.http.HttpClient at java.base/java.net.URLClassLoader.findClass(URLClassLoader.java:476) at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:589) at org.apache.flink.util.FlinkUserCodeClassLoader.loadClassWithoutExceptionHandling(FlinkUserCodeClassLoader.java:67) at org.apache.flink.util.ChildFirstClassLoader.loadClassWithoutExceptionHandling(ChildFirstClassLoader.java:74) at org.apache.flink.util.FlinkUserCodeClassLoader.loadClass(FlinkUserCodeClassLoader.java:51) at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:522)