Hi Team, 1. I have a Pinot Server receiving requests for segments it does not own. The server is reporting exception processing errors and slow query processing time 2. Is it normal in a 3 broker setup where only 2 of the 3 brokers are making requests query requests

Hello, thought i'd post here before continuing further debugging. We're upgrading out Pinot installation and it's been a while so we have to move to the newer bitnami zookeeper chart. I've done the upgrade in our sandbox env and everything seemed to go smoothly, no data loss and components recovered just fine. However, when proceeding to our dev env, post restart and recreation of pods, we seem to have lost important zookeeper data - specifically table and schema configs. I see snapshots in the

/bitnami/zookeeper/data

dir, so clearly some things were not lost, but curious if migrating charts requires some extra steps in the config. Also, couple of followup questions: • are there ways to recover the tables/schemas if zookeeper lost them on restart? • how can this happen in one env but not in another? the only difference i can think of is the addition of basic auth to the controller ui • ways to prevent this for the future? we want to update prod as well, but not sure how to prevent this scenario. Backing up tables/schemas manually is one thing, but is there other important data whose loss can prevent a healthy recovery of pinot?

Hi team, We have a realtime table in Pinot cluster. We want to migrate the realtime data to another Pinot cluster. is it possible to load the COMPLETED segments into new cluster somehow? Pinot version: 1.0

Hi team, does Kafka ingestion support zstd decompression?

Hi team , I am facing issues when trying to enable multistage engine in pinot UI , and the error message is not very clear attaching snippet , looking forward to get help to diagnose the issue . It says table does not exist but it does.

I'm experimenting and trying to load in data into a realtime table that is very "tall", with only about 10 columns but hundreds of millions of rows. I'm seeing server restarts:

pod/pinot-server-0                           1/1     Running     0               43h
pod/pinot-server-1                           1/1     Running     0               43h
pod/pinot-server-2                           1/1     Running     1 (26s ago)     43h
pod/pinot-server-3                           1/1     Running     0               43h
pod/pinot-server-4                           1/1     Running     0               43h
pod/pinot-server-5                           0/1     OOMKilled   3 (3m56s ago)   43h
pod/pinot-server-6                           1/1     Running     1 (8m50s ago)   81m
pod/pinot-server-7                           1/1     Running     1 (7m44s ago)   81m

The table data itself is not that large, pretty small in fact (at 10GB currently), there are 8 servers with O(60GB) memory each, 100GB PVCs, and a total of maybe 450 segments over 4 tables. But this table is (IIUC) trying to do some pretty high cardinality upserts, easily into the many tens of millions of keys. Could this be the cause of the OOMs? Are there specific settings I can review or actions I can take while I'm learning besides larger instances?

Hi team, I want to know a few things: what will happen if we increase the number of replicas from 2 to 3 of pinot with this values.yaml

image:
 repository: <http://615177075440.dkr.ecr.ap-south-1.amazonaws.com/pinot|615177075440.dkr.ecr.ap-south-1.amazonaws.com/pinot>
 tag: 1.0.1
 pullPolicy: IfNotPresent

cluster:
 name: pinot-prod

# ----------------------------------------------------------------------------
# ZOOKEEPER: 3 replicas
# ----------------------------------------------------------------------------
zookeeper:
 name: pinot-zookeeper
 replicaCount: 3
 persistence:
  enabled:   true
  storageClass: gp3   # ← GP3 EBS
  size:     10Gi
 resources:
  requests:
   cpu:  100m
   memory: 256Mi
  limits:
   cpu:  300m
   memory: 512Mi

 port: 2181

# ----------------------------------------------------------------------------
# CONTROLLER: 2 replicas, internal LB
# ----------------------------------------------------------------------------
controller:
 name: pinot-controller
 replicaCount: 2
 startCommand: "StartController"
 # podManagementPolicy: Parallel
 resources:
  requests:
   cpu:  100m
   memory: 1Gi
  limits:
   cpu:  300m
   memory: 3Gi
  
 jvmOpts: "-javaagent:/opt/pinot/etc/jmx_prometheus_javaagent/jmx_prometheus_javaagent.jar=9010:/opt/pinot/etc/jmx_prometheus_javaagent/configs/pinot.yml -XX:ActiveProcessorCount=2 -Xms512M -Xmx2G -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -Xlog:gc*:file=/opt/pinot/gc-pinot-controller.log -Djute.maxbuffer=4000000"
   
 # Persist controller metadata
 persistence:
  enabled:   true
  accessMode:  ReadWriteOnce
  storageClass: gp3
  size:     50Gi
  mountPath:  /var/pinot/controller/data

 service:
  name: controller
  annotations:
   <http://prometheus.io/scrape|prometheus.io/scrape>: "true"
   <http://prometheus.io/path|prometheus.io/path>: /metrics
   <http://prometheus.io/port|prometheus.io/port>: "9010"
  # labels:
  #  prometheus-monitor: "true"
  extraPorts:
   - name: controller-prom
    protocol: TCP
    containerPort: 9010
   
   
 podAnnotations:
  <http://prometheus.io/scrape|prometheus.io/scrape>: "true"
  <http://prometheus.io/path|prometheus.io/path>: /metrics
  <http://prometheus.io/port|prometheus.io/port>: "9010"

 # Expose via Kubernetes Ingress on port 9000
 # ingress:
 #  v1:
 #   enabled: true
 #   ingressClassName: nginx     # or your ingress controller
 #   annotations:
 #    <http://nginx.ingress.kubernetes.io/backend-protocol|nginx.ingress.kubernetes.io/backend-protocol>: "HTTP"
 #    <http://nginx.ingress.kubernetes.io/rewrite-target|nginx.ingress.kubernetes.io/rewrite-target>: /
 #   hosts: [<http://pinot-eks.sr-bi-internal.in|pinot-eks.sr-bi-internal.in>]
 #   path: /controller
 #   tls: []
 external:
  enabled: false

# ----------------------------------------------------------------------------
# BROKER: 2 replicas, internal LB
# ----------------------------------------------------------------------------
broker:
 name: pinot-broker
 startCommand: "StartBroker"
 # podManagementPolicy: Parallel
 replicaCount: 2

 resources:
  requests:
   cpu:  200m
   memory: 1Gi
  limits:
   cpu:  500m
   memory: 3Gi

 jvmOpts: "-javaagent:/opt/pinot/etc/jmx_prometheus_javaagent/jmx_prometheus_javaagent.jar=9020:/opt/pinot/etc/jmx_prometheus_javaagent/configs/pinot.yml -XX:ActiveProcessorCount=2 -Xms512M -Xmx2G -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -Xlog:gc*:file=/opt/pinot/gc-pinot-broker.log -Djute.maxbuffer=4000000"

 service:
  name: broker
  # type: LoadBalancer
  annotations:
   # <http://service.beta.kubernetes.io/aws-load-balancer-internal|service.beta.kubernetes.io/aws-load-balancer-internal>: "true"
   <http://prometheus.io/scrape|prometheus.io/scrape>: "true"
   <http://prometheus.io/path|prometheus.io/path>: /metrics
   <http://prometheus.io/port|prometheus.io/port>: "9020"
  # labels:
  #  prometheus-monitor: "true"
  extraPorts:
   - name: broker-prom
    protocol: TCP
    containerPort: 9020
   
 podAnnotations:
  <http://prometheus.io/scrape|prometheus.io/scrape>: "true"
  <http://prometheus.io/path|prometheus.io/path>: /metrics
  <http://prometheus.io/port|prometheus.io/port>: "9020"

 # Expose via Kubernetes Ingress on port 8099
 # ingress:
 #  v1:
 #   enabled: true
 #   ingressClassName: nginx     # or your ingress controller
 #   annotations:
 #    <http://nginx.ingress.kubernetes.io/backend-protocol|nginx.ingress.kubernetes.io/backend-protocol>: "HTTP"
 #    <http://nginx.ingress.kubernetes.io/use-regex|nginx.ingress.kubernetes.io/use-regex>: "true"
 #    <http://nginx.ingress.kubernetes.io/rewrite-target|nginx.ingress.kubernetes.io/rewrite-target>: /$2
 #   hosts: [<http://pinot-eks.sr-bi-internal.in|pinot-eks.sr-bi-internal.in>]
 #   path: /broker(/|$)(.*)
 #   pathType: ImplementationSpecific
 #   tls: []
 external:
  enabled: false


# ----------------------------------------------------------------------------
# PINOT SERVER: 2 replicas, each with 100 Gi gp3 PVC
# ----------------------------------------------------------------------------
server:
 name: pinot-server
 startCommand: "StartServer"
 # podManagementPolicy: Parallel
 replicaCount: 2
  
 resources:
  requests:
   cpu:  2000m  # 2 vCPU
   memory: 5Gi
  limits:
   cpu:  4000m  # 4 vCPU
   memory: 10Gi

 persistence:
  enabled: true
  accessMode: ReadWriteOnce
  size: 100G
  mountPath: /var/pinot/server/data
  storageClass: gp3
  
 jvmOpts: "-javaagent:/opt/pinot/etc/jmx_prometheus_javaagent/jmx_prometheus_javaagent.jar=9030:/opt/pinot/etc/jmx_prometheus_javaagent/configs/pinot.yml -Xms4G -Xmx8G -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -Xlog:gc*:file=/opt/pinot/gc-pinot-server.log -Djute.maxbuffer=4000000"

 service:
  name: server
  # type: LoadBalancer
  annotations:
   # <http://service.beta.kubernetes.io/aws-load-balancer-internal|service.beta.kubernetes.io/aws-load-balancer-internal>: "true"
   <http://prometheus.io/scrape|prometheus.io/scrape>: "true"
   <http://prometheus.io/path|prometheus.io/path>: /metrics
   <http://prometheus.io/port|prometheus.io/port>: "9030"
  # labels:
  #  prometheus-monitor: "true"
  extraPorts:
   - name: server-prom
    protocol: TCP
    containerPort: 9030
   
 podAnnotations:
  <http://prometheus.io/scrape|prometheus.io/scrape>: "true"
  <http://prometheus.io/path|prometheus.io/path>: /metrics
  <http://prometheus.io/port|prometheus.io/port>: "9030"


# ----------------------------------------------------------------------------
# MINION: 1 replica (for background tasks / retention, compaction, etc.)
# ----------------------------------------------------------------------------
minion:
 enabled: true      # run the minion pod
 name: pinot-minion
 startCommand: "StartMinion"
 # podManagementPolicy: Parallel
 replicaCount: 1     # scale up if you have heavy compaction/merge workloads

 resources:
  requests:
   cpu:  100m
   memory: 512Mi
  limits:
   cpu:  200m
   memory: 1Gi

 jvmOpts: "-javaagent:/opt/pinot/etc/jmx_prometheus_javaagent/jmx_prometheus_javaagent.jar=8008:/opt/pinot/etc/jmx_prometheus_javaagent/configs/pinot.yml -XX:ActiveProcessorCount=2 -Xms256M -Xmx1G -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -Xlog:gc*:file=/opt/pinot/gc-pinot-minion.log -Djute.maxbuffer=4000000"

I am running pinot EKS with 3 nodes but utilizing only 2 as the number of replicas are two only..... I want to use 3 nodes for better performance what will happen if I increase the number of pods to 3 and how should I do it with the existing data not getting lost? @Xiang Fu @Mayank

You need to tag the new instances and run rebalance

Hello during query performance testing we found out that most of our queries spend a lot of time in steps that doesn't really make sense, can you shred some light into if it is possible to optimize those steps or it is normal behavior? Our queries were using the V1 engine (without multistage) and are simple sum, avg, min, max aggregations per customer_id (we have partitioning for it, so pinot scans relatively small amounts of data) and returning between 1 and 10 rows per query, where most of the queries also had a simple group by 1 column without ordering after that. If you need more info let me know

Hello, I want to know a few architectural things about pinot segments transition from realtime to offline, how does it work? and which config is used for that?

Hello Team, We are currently using Apache Pinot on AWS EKS and are in the process of deploying a multi-tenant setup. As part of this, we’ve added 2 servers and 2 brokers, and tagged them appropriately to reflect a new tenant. We were able to successfully: 1. Create a Pinot table assigned to the new tenant 2. See all table segments in GOOD status 3. View the new tenant's brokers and servers correctly listed in the Pinot Web UI after tagging tenent. However, we’re encountering an issue while querying the table. The query fails with the following error: {"requestId":"33806233000000000","brokerId":"Broker_pinot-sr-broker-0.pinot-sr-broker.pinot.svc.cluster.local_8099","exceptions":[{"errorCode":410,"message":"BrokerResourceMissingError"}],"numServersQueried":0,"numServersResponded":0,"numSegmentsQueried":0,"numSegmentsProcessed":0,"numSegmentsMatched":0,"numConsumingSegmentsQueried":0,"numConsumingSegmentsProcessed":0,"numConsumingSegmentsMatched":0,"numDocsScanned":0,"numEntriesScannedInFilter":0...} In Controller UI we are getting below error message: Error Code: 450 InternalError: java.net.UnknownHostException: pinot-sr-broker-1.pinot-sr-broker.pinot.svc.cluster.local at java.base/java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:229) at java.base/java.net.Socket.connect(Socket.java:609) at java.base/sun.net.NetworkClient.doConnect(NetworkClient.java:182) Attaching the deployment files used:

Hi team, this size that is shown here is the size of each replica? or it is the actual size of data?

Hi 😉 I’m still on an old pinot version 0.12 (migration is planned but I need a bit more robustness before) First things to look at is S3 as deepstore I’ve folowed the doc here https://docs.pinot.apache.org/release-0.12.0/users/tutorials/use-s3-as-deep-store-for-pinot From Swagger controller seems able to download the segment when I hit th download API but on server side lots of Failed to download segment absencesreport__1__5__20240527T2122Z from deep store: Download segment absencesreport__1__5__20240527T2122Z from deepstore uri s3://bucketName/segments/absencesreport_REALTIME/absencesreport__1__5__20240527T2122Z failed. Caught exception in state transition from OFFLINE -> ONLINE for resource: absencesreport_REALTIME, partition: absencesreport__1__5__20240527T2122Z Any ideas ?

getting logs like software.amazon.awssdk.services.s3.model.S3Exception: The authorization header is malformed; the region is wrong; expecting 'eu-west-1'. (Service: S3, Status Code: 400, Request ID: 184BA1F70B628FA6, Extended Request ID: 82b9e6b1548ad0837abe6ff674d1d3e982a2038442a1059f595d95962627f827)

here is my server conf for the S3 part

# Pinot Server Data Directory
pinot.server.instance.dataDir=/var/lib/pinot_data/server/index
# Pinot Server Temporary Segment Tar Directory
pinot.server.instance.segmentTarDir=/var/lib/pinot_data/server/segmentTar
#S3
pinot.server.storage.factory.class.s3=org.apache.pinot.plugin.filesystem.S3PinotFS
pinot.server.storage.factory.s3.region=us-west-1
pinot.server.segment.fetcher.protocols=file,http,s3
pinot.server.storage.factory.s3.bucket.name=bucketName
pinot.server.storage.factory.s3.endpoint=URL_OF_MY_S3_ENDOINT
pinot.server.segment.fetcher.s3.class=org.apache.pinot.common.utils.fetcher.PinotFSSegmentFetcher
pinot.server.segment.fetcher.s3.pathStyleAccess=true

Any ideas welcome 🙂

I have a highly aggregated real-time table that I’m using to query and chart statistics. Although I’ve added around 10 billion events, they’re aggregated(upserted) into about 500,000 rows. Despite this, the table currently takes up around 200 GB of storage. However, if I export the entire table using

SELECT * FROM table

and then re-import it using a simple tool, the size drops to just 15 MB. I only need the aggregated data — I don’t need per-event details. Is there a way to merge the old segments and significantly reduce table size and improve query speed using Pinot tasks?

Hi Team, I'm on pinot 1.3 and trying out the multi topic ingestion in a single pinot table. I've configured my table as shown below

"streamIngestionConfig": {
        "streamConfigMaps": [
          {
            "streamType": "kafka",
            "stream.kafka.topic.name": "flattened_spans2",
            "stream.kafka.broker.list": "kafka:9092",
            "stream.kafka.consumer.type": "lowlevel",
            "stream.kafka.consumer.prop.auto.offset.reset": "smallest",
            "stream.kafka.consumer.factory.class.name": "org.apache.pinot.plugin.stream.kafka20.KafkaConsumerFactory",
            "stream.kafka.decoder.class.name": "org.apache.pinot.plugin.stream.kafka.KafkaJSONMessageDecoder",
            "realtime.segment.flush.threshold.rows": "0",
            "realtime.segment.flush.threshold.time": "30m",
            "realtime.segment.flush.threshold.segment.size": "300M"
          },
          {
            "streamType": "kafka",
            "stream.kafka.topic.name": "flattened_spans3",
            "stream.kafka.broker.list": "kafka.pinot-0-nfr-setup.svc.cluster.local:9092",
            "stream.kafka.consumer.type": "lowlevel",
            "stream.kafka.consumer.prop.auto.offset.reset": "smallest",
            "stream.kafka.consumer.factory.class.name": "org.apache.pinot.plugin.stream.kafka20.KafkaConsumerFactory",
            "stream.kafka.decoder.class.name": "org.apache.pinot.plugin.stream.kafka.KafkaJSONMessageDecoder",
            "realtime.segment.flush.threshold.rows": "0",
            "realtime.segment.flush.threshold.time": "30m",
            "realtime.segment.flush.threshold.segment.size": "300M"
          }
        ]
      }

But i am running into this issue.

First kafka
2025/06/20 13:21:17.528 INFO [KafkaConsumer] [otel_spans__1__0__20250620T1321Z] [Consumer clientId=otel_spans_REALTIME-flattened_spans2-1, groupId=null] Seeking to offset 0 for partition flattened_spans2-1

Second kafka
025/06/20 13:22:08.659 INFO [KafkaConsumer] [otel_spans__10001__0__20250620T1321Z] [Consumer clientId=otel_spans_REALTIME-flattened_spans3-1, groupId=null] Seeking to offset 0 for partition flattened_spans3-10001
2025/06/20 13:22:08.659 INFO [KafkaConsumer] [otel_spans__10000__0__20250620T1321Z] [Consumer clientId=otel_spans_REALTIME-flattened_spans3-0, groupId=null] Seeking to offset 0 for partition flattened_spans3-10000

the flattened_spans3 has only partitions 1-3 but the pinot server is seeking out partition number 10000 for some reason. Can someone please guide me on where i'm going wrong with my config ?

Hi Team Pinot server went down when checked it failed with following error in screenshot. Is it because of memory issue ? Will i loss data if i restart the server with following command ?

bin/pinot-admin.sh StartServer -configFileName conf/pinot-server.conf

Hi team, I'm trying to run a

MergeRollupTask

on the

sales_OFFLINE

table, but it fails with a

StringIndexOutOfBoundsException

. It looks like the error comes from this line:

MergeRollupTaskUtils.getLevelToConfigMap()

Here, is the config that I am using.

json

j
"taskTypeConfigsMap": {
  "MergeRollupTask": {
    "mergeType": "rollup",
    "bucketTimePeriod": "1d",
    "bufferTimePeriod": "3d",
    "revenue.aggregationType": "sum",
    "quantity.aggregationType": "sum"
  }
}

And here's the relevant part of the error:

java.lang.StringIndexOutOfBoundsException: begin 0, end -1, length 9
at ...MergeRollupTaskUtils.getLevelToConfigMap(MergeRollupTaskUtils.java:64)

Hi Team, DOES PINOT SUPPORTS ADLS Gen 2 (wasbs) or it only supports abfss I am writing parquet files to the azure container, using wasbs method. Then i use this ingestionconfig to ingest it to pinot, using minions: "ingestionConfig": { "batchIngestionConfig": { "segmentIngestionType": "APPEND", "segmentIngestionFrequency": "DAILY", "consistentDataPush": False, "batchConfigMaps": [ { "input.fs.className": "org.apache.pinot.plugin.filesystem.ADLSGen2PinotFS", "input.fs.prop.authenticationType": "ACCESS_KEY", "input.fs.prop.accountName": "wzanalyticsdatastoreprod", "input.fs.prop.accessKey": "xxxxxxxxxxx", "input.fs.prop.fileSystemName": tenant_id, "inputDirURI": f"wasbs://{tenant_id}@wzanalyticsdatastoreprod.blob.core.windows.net/pinot", "includeFileNamePattern": "glob:**/*.parquet", "excludeFileNamePattern": "glob:**/*.tmp", "inputFormat": "parquet" } ] } But I think pinot is not able to look into specified BLOB. I cant use abfss in this container cause does not support BlobStorageEvents or SoftDelete In my DEV container, i was writing the parquet in abfss methos, it is still working.. Is something wrong in my ingestionConfig, using wasbs. can someone pls help!!

Hi team, I'm trying to download segments from one Pinot table and use them in a different table that has the same schema but a different retention configuration. Currently, I'm encountering an issue where the metadata doesn't match because the tables have different names.

Hi team, first time here. I have an issue when trying to update a table via API. The update is not being applied.

hi guys.. has anyone faced this recurring message on your logs? We are seeing this for some time in our pre prod envs despite following the configuration settings as described in the documentation

The configuration 'stream.kafka.isolation.level' was supplied but isn't a known config.

https://docs.pinot.apache.org/manage-data/data-import/batch-ingestion/dim-table im looking into Dimensions table currently and noticed that it requires

primaryKeyColumns

, based on my experience on upsert table, primary key metadata TTL was stored on heap and as number of records and primary keys grows, memory/RAM usage will increase too. do i need to expect this kind of situation too on dimension table? and does dimension table can be a realtime table rather than offline so i can push the data through kafka ? our app architecture is kinda complex right now. we need a table to stores product activity logs, kind of product tracking such as example

stock increase

,

price increment

and etc. and in some cases there are ingestion that was duplicated like in the same day it will be pushed more than 1 time to kafka, causing duplicate. by right we do not need full product data, we just need the changes like the example i shared and what are the id of the changes so we can check historically for this particular product what was changed. i tested using upsert since its the most near to my use case but the memory usage was very huge and our pinot ec2 server was going downtime from time to time bcs of upsert table due to out of memory error. i really appreciate if any of you guys can share any config that you guys work on / whatever i can do to tune my config / improve our ingestion to pinot

Hi all, I have ran into an issue with pinot minion with kerberized hdfs where pinot minion upsert tasks fails with below error:

UI:
org.apache.pinot.spi.utils.retry.AttemptsExceededException: Operation failed after 3 attempts
	at org.apache.pinot.spi.utils.retry.BaseRetryPolicy.attempt(BaseRetryPolicy.java:65)
	at org.apache.pinot.common.utils.fetcher.BaseSegmentFetcher.fetchSegmentToLocal(BaseSegmentFetcher.java:74)
	at org.apache.pinot.common.utils.fetcher.SegmentFetcherFactory.fetchSegmentToLocal(SegmentFetcherFactory.java:124)
	at org.apache.pinot.common.utils.fetcher.SegmentFetcherFactory.fetchSegmentToLocal(SegmentFetcherFactory.java:132)
	at org.apache.pinot.common.utils.fetcher.SegmentFetcherFactory.fetchAndDecryptSegmentToLocal(SegmentFetcherFactory.java:165)
	at org.apache.pinot.plugin.minion.tasks.BaseTaskExecutor.downloadSegmentToLocal(BaseTaskExecutor.java:121)
	at org.apache.pinot.plugin.minion.tasks.BaseSingleSegmentConversionExecutor.executeTask(BaseSingleSegmentConversionExecutor.java:105)
	at org.apache.pinot.plugin.minion.tasks.BaseSingleSegmentConversionExecutor.executeTask(BaseSingleSegmentConv

Minion log shows:
2025/07/02 13:23:21.309 WARN [PinotFSSegmentFetcher] [TaskStateModelFactory-task_thread-3] Caught exception while fetching segment from: <hdfs://xxxxxxx/controller_data/xxxxxxx/xxxxxxx__4__648__20250528T1621Z> to: /tmp/PinotMinion/data/UpsertCompactionTask/tmp-9727a6d3-cc2d-44d0-9666-34939abbc356/tarredSegment
org.apache.hadoop.security.AccessControlException: SIMPLE authentication is not enabled.  Available:[TOKEN, KERBEROS]
        at jdk.internal.reflect.GeneratedConstructorAccessor43.newInstance(Unknown Source) ~[?:?]
        at java.base/jdk.internal.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) ~[?:?]
        at java.base/java.lang.reflect.Constructor.newInstance(Constructor.java:490) ~[?:?]
        at org.apache.hadoop.ipc.RemoteException.instantiateException(RemoteException.java:121) ~[pinot-parquet-1.2.0-shaded.jar:1.2.0-cc33ac502a02e2fe830fe21e556234ee99351a7a]
        at org.apache.hadoop.ipc.RemoteException.unwrapRemoteException(RemoteException.java:88) ~[pinot-parquet-1.2.0-shaded.jar:1.2.0-cc33ac502a02e2fe830fe21e556234ee99351a7a]
        at org.apache.hadoop.hdfs.DFSClient.getFileInfo(DFSClient.java:1741) ~[pinot-orc-1.2.0-shaded.jar:1.2.0-cc33ac502a02e2fe830fe21e556234ee99351a7a]
        at org.apache.hadoop.hdfs.DistributedFileSystem$29.doCall(DistributedFileSystem.java:1829) ~[pinot-orc-1.2.0-shaded.jar:1.2.0-cc33ac502a02e2fe830fe21e556234ee99351a7a]
        at org.apache.hadoop.hdfs.DistributedFileSystem$29.doCall(DistributedFileSystem.java:1826) ~[pinot-orc-1.2.0-shaded.jar:1.2.0-cc33ac502a02e2fe830fe21e556234ee99351a7a]
        at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81) ~[pinot-parquet-1.2.0-shaded.jar:1.2.0-cc33ac502a02e2fe830fe21e556234ee99351a7a]
        at org.apache.hadoop.hdfs.DistributedFil

Pinot Server, Broker, and Controller are all able to read/write segments from HDFS using the configured keytab. I have recently added 3 Pinot Minion on new nodes, configured with the same keytab, principal, and Hadoop config path. However, when the Minion runs tasks like UpsertCompaction, it fails with the above error: Minion runs under pinot user (systemd) kinit is successful, and Kerberos ticket is visible via klist

pinot.minion.segment.fetcher.hdfs.hadoop.kerberos.principal=xxxxxx@xxxxxx

pinot.minion.segment.fetcher.hdfs.hadoop.kerberos.keytab=/etc/security/keytabs/pinot.keytab

pinot.minion.storage.factory.hdfs.hadoop.conf.path=/usr/hdp/xxxxx/hadoop/conf

Is there anything else Pinot Minion needs to perform Kerberos login internally? Does it require JAAS config explicitly even with keytab/principal settings?

Hi team, in one of my cluster, the ingestion rate decreases after some time of rebalancing and it comes to zero after a few time. what could be the reason? I am running realtime table only but this bug is happening a lot of time

Hi Team, Is there any way to find duplicate segments

Hi all, Can anyone help me, with this error Not able to query table in pinot

Error Code: 305
null:
18 segments unavailable, sampling 10: [iptv_events_test__8__0__20250708T0323Z, iptv_events_test__10__0__20250708T0323Z, iptv_events_test__11__0__20250708T0323Z, iptv_events_test__9__0__20250708T0323Z, iptv_events_test__6__0__20250708T0323Z, iptv_events_test__7__0__20250708T0323Z, iptv_events_test__0__0__20250708T0323Z, iptv_events_test__5__0__20250708T0323Z, iptv_events_test__1__0__20250708T0323Z, iptv_events_test__16__0__20250708T0323Z]N

Screenshot 2025-07-08 at 13.27.22.png

Let me know if we can connect on this

Hi pinot folks! I have a question related to

SegmentTarPush

data ingestion jobs. I have segments stored in GCS that I want to upload to my offline table. There was an issue with my table config early on that prevented my

RealtimeToOfflineSegmentsTask

from working properly. Now the segments have been removed from my realtime table (retention date passed), but haven't been uploaded to the offline table. Because I have a GCS deep store configured, those segments that were removed from my realtime table still exist in GCS. So I want to run the

pinot-admin.sh

LaunchDataIngestionJob

command to upload those segments to my offline table. I have written the following job spec:

executionFrameworkSpec:
  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'
  segmentMetadataPushJobRunnerClassName: 'org.apache.pinot.plugin.ingestion.batch.standalone.SegmentMetadataPushJobRunner'
jobType: SegmentTarPush
inputDirURI: 'gs:://my_bucket/my_table_folder'
outputDirURI: 'gs:://my_bucket/my_table_folder'
overwriteOutput: true
pinotFSSpecs:
  - scheme: gs
    className: org.apache.pinot.plugin.filesystem.GcsPinotFS
tableSpec:
  tableName: 'my_table_OFFLINE'
pinotClusterSpecs:
  - controllerURI: '<http://my_controller_url.com>'
pushJobSpec:
  pushAttempts: 2
  pushRetryIntervalMillis: 1000

Am I using the right job type for what I'm trying to achieve? Is what I'm trying to do possible?