When data is pushed in to Pinot, it makes a backup copy of the data and stores it on the configured deep-storage (S3/GCP/ADLS/NFS/etc). This copy is stored as tar.gz Pinot segments. Note, that pinot servers keep a (untarred) copy of the segments on their local disk as well. This is done for performance reasons.
How does Pinot use Zookeeper?
Pinot uses Apache Helix for cluster management, which in turn is built on top of Zookeeper. Helix uses Zookeeper to store the cluster state, including Ideal State, External View, Participants, etc. Besides that, Pinot uses Zookeeper to store other information such as Table configs, schema, Segment Metadata, etc.
Why am I getting "Could not find or load class" error when running Quickstart using 0.8.0 release?
Please check the JDK version you are using. The release 0.8.0 binary is on JDK 11. You may be getting this error if you are using JDK8. In that case, please consider using JDK11, or you will need to download the for the release and it locally.
This page has a collection of frequently asked questions with answers from the community.
This is a list of frequent questions most often asked in our troubleshooting channel on Slack. Please feel free to contribute your questions and answers here and make a pull request.
I get the following error when running a query, what does it mean?
This essentially implies that the Pinot Broker assigned to the table specified in the query was not found. A common root cause for this is a typo in the table name in the query. Another uncommon reason could be if there wasn't actually a broker with required broker tenant tag for the table.
What are all the fields in the Pinot query's JSON response?
Here's the page explaining the Pinot response format:
SQL Query fails with "Encountered 'timestamp' was expecting one of..."
"timestamp" is a reserved keyword in SQL. Escape timestamp with double quotes.
Other commonly encountered reserved keywords are date, time, table.
Filtering on STRING column WHERE column = "foo" does not work?
For filtering on STRING columns, use single quotes
ORDER BY using an alias doesn't work?
The fields in the ORDER BY clause must be one of the group by clauses or aggregations, BEFORE applying the alias. Therefore, this will not work
Instead, this will work
Does pagination work in GROUP BY queries?
No. Pagination only works for SELECTION queries
How do I increase timeout for a query ?
You can add this at the end of your query: option(timeoutMs=X). For eg: the following example will use a timeout of 20 seconds for the query:
You can also use SET "timeoutMs" = 20000; SELECT COUNT(*) from myTable
For changing timeout on the entire cluster, set this property pinot.broker.timeoutMs in either broker configs or cluster configs (using POST /cluster/configs API from swagger)
How do I cancel a query?
Add these two configs for Pinot server and broker to start tracking of running queries. The query tracks are added and cleaned as query starts and ends, so should not consume much resource.
Then use the Rest APIs on Pinot controller to list running queries and cancel them via the query ID and broker ID (as query ID is only local to broker), like below:
How do I optimize my Pinot table for doing aggregations and group-by on high cardinality columns ?
In order to speed up aggregations, you can enable metrics aggregation on the required column by adding a in the corresponding schema and setting aggregateMetrics to true in the table config. You can also use a star-tree index config for such columns ()
How do I verify that an index is created on a particular column ?
There are 2 ways to verify this:
Log in to a server that hosts segments of this table. Inside the data directory, locate the segment directory for this table. In this directory, there is a file named index_map which lists all the indexes and other data structures created for each segment. Verify that the requested index is present here.
During query: Use the column in the filter predicate and check the value of numEntriesScannedInFilter . If this value is 0, then indexing is working as expected (works for Inverted index)
Does Pinot use a default value for LIMIT in queries?
Yes, Pinot uses a default value of LIMIT 10 in queries. The reason behind this default value is to avoid unintentionally submitting expensive queries that end up fetching or processing a lot of data from Pinot. Users can always overwrite this by explicitly specifying a LIMIT value.
Does Pinot cache query results?
Pinot does not cache query results, each query is computed in its entirety. Note though, running the same or similar query multiple times will naturally pull in segment pages into memory making subsequent calls faster. Also, for realtime systems, the data is changing in realtime, so results cannot be cached. For offline-only systems, caching layer can be built on top of Pinot, with invalidation mechanism built-in to invalidate the cache when data is pushed into Pinot.
I'm noticing that the first query is slower than subsequent queries, why is that?
Pinot memory maps segments. It warms up during the first query, when segments are pulled into the memory by the OS. Subsequent queries will have the segment already loaded in memory, and hence will be faster. The OS is responsible for bringing the segments into memory, and also removing them in favor of other segments when other segments not already in memory are accessed.
How do I determine if StarTree index is being used for my query?
The query execution engine will prefer to use StarTree index for all queries where it can be used. The criteria to determine whether StarTree index can be used is as follows:
All aggregation function + column pairs in the query must exist in the StarTree index.
All dimensions that appear in filter predicates and group-by should be StarTree dimensions.
For queries where above is true, StarTree index is used. For other queries, the execution engine will default to using the next best index available.
SELECT count(colA) as aliasA, colA from tableA GROUP BY colA ORDER BY aliasA
SELECT count(colA) as sumA, colA from tableA GROUP BY colA ORDER BY count(colA)
SELECT COUNT(*) from myTable option(timeoutMs=20000)
pinot.server.enable.query.cancellation=true // false by default
pinot.broker.enable.query.cancellation=true // false by default
GET /queries: to show running queries as tracked by all brokers
Response example: `{
"Broker_192.168.0.105_8000": {
"7": "select G_old from baseballStats limit 10",
"8": "select G_old from baseballStats limit 100"
}
}`
DELETE /query/{brokerId}/{queryId}[?verbose=false/true]: to cancel a running query
with queryId and brokerId. The verbose is false by default, but if set to true,
responses from servers running the query also return.
Response example: `Cancelled query: 8 with responses from servers:
{192.168.0.105:7501=404, 192.168.0.105:7502=200, 192.168.0.105:7500=200}`
Operations FAQ
Memory
How much heap should I allocate for my Pinot instances?
Typically, Pinot components try to use as much off-heap (MMAP/DirectMemory) wherever possible. For example, Pinot servers load segments in memory-mapped files in MMAP mode (recommended), or direct memory in HEAP mode. Heap memory is used mostly for query execution and storing some metadata. We have seen production deployments with high throughput and low-latency work well with just 16 GB of heap for Pinot servers and brokers. Pinot controller may also cache some metadata (table configs etc) in heap, so if there are just a few tables in the Pinot cluster, a few GB of heap should suffice.
DR
Does Pinot provide any backup/restore mechanism?
Pinot relies on deep-storage for storing backup copy of segments (offline as well as realtime). It relies on Zookeeper to store metadata (table configs, schema, cluster state, etc). It does not explicitly provide tools to take backups or restore these data, but relies on the deep-storage (ADLS/S3/GCP/etc), and ZK to persist these data/metadata.
Alter Table
Can I change a column name in my table, without losing data?
Changing a column name or data type is considered backward incompatible change. While Pinot does support schema evolution for backward compatible changes, it does not support backward incompatible changes like changing name/data-type of a column.
How to change number of replicas of a table?
You can change the number of replicas by updating the table config's section. Make sure you have at least as many servers as the replication.
For OFFLINE table, update
For REALTIME table update
After changing the replication, run a .
Rebalance
How to run a rebalance on a table?
Refer to .
Why does my REALTIME table not use the new nodes I added to the cluster?
Likely explanation: num partitions * num replicas < num servers
In realtime tables, segments of the same partition always continue to remain on the same node. This sticky assignment is needed for replica groups and is critical if using upserts. For instance, if you have 3 partitions, 1 replica, and 4 nodes, only ¾ nodes will be used, and all of p0 segments will be on 1 node, p1 on 1 node, and p2 on 1 node. One server will be unused, and will remain unused through rebalances.
There’s nothing we can do about CONSUMING segments, they will continue to use only 3 nodes if you have 3 partitions. But we can rebalance such that completed segments use all nodes. If you want to force the completed segments of the table to use the new server, use this config
Segments
How to control number of segments generated?
The number of segments generated depends on the number of input files. If you provide only 1 input file, you will get 1 segment. If you break up the input file into multiple files, you will get as many segments as the input files.
What are the common reasons my segment is in a BAD state ?
This typically happens when the server is unable to load the segment. Possible causes: Out-Of-Memory, no-disk space, unable to download segment from deep-store, and similar other errors. Please check server logs for more information.
How to reset a segment when it runs into a BAD state?
Use the segment reset controller REST API to reset the segment:
How to pause realtime ingestion?
Refer to .
What's the difference to Reset, Refresh, or Reload a segment?
RESET: this gets a segment in ERROR state back to ONLINE or CONSUMING state. Behind the scenes, Pinot controller takes the segment to OFFLINE state, waits for External View to stabilize, and then moves it back to ONLINE/CONSUMING state, thus effectively resetting segments or consumers in error states.
REFRESH: this replaces the segment with a new one, with the same name but often different data. Under the hood, Pinot controller sets new segment metadata in Zookeeper, and notifies brokers and servers to check their local states about this segment and update accordingly. Servers also download the new segment to replace the old one, when both have different checksums. There is no separate rest API for refreshing, and it is done as part of SegmentUpload API today.
RELOAD: this reloads the segment, often to generate a new index as updated in table config. Underlying, Pinot server gets the new table config from Zookeeper, and uses it to guide the segment reloading. In fact, the last step of REFRESH as explained above is to load the segment into memory to serve queries. There is a dedicated rest API for reloading. By default, it doesn't download segment. But option is provided to force server to download segment to replace the local one cleanly.
In addition, RESET brings the segment OFFLINE temporarily; while REFRESH and RELOAD swap the segment on server atomically without bringing down the segment or affecting ongoing queries.
Tenants
How can I make brokers/servers join the cluster without the DefaultTenant tag?
Set this property in your controller.conf file
Now your brokers and servers should join the cluster as broker_untagged and server_untagged . You can then directly use the POST /tenants API to create the desired tenants
Minion
How to tune minion task timeout and parallelism on each worker
There are two task configs but set as part of cluster configs like below. One controls task's overall timeout (1hr by default) and one for how many tasks to run on a single minion worker (1 by default). The <taskType> is the task to tune, e.g. MergeRollupTask or RealtimeToOfflineSegmentsTask etc.
How to I manually run a Periodic Task
Refer to
Tuning and Optimizations
Do replica groups work for real-time?
Yes, replica groups work for realtime. There's 2 parts to enabling replica groups:
Replica groups segment assignment
Replica group query routing
Replica group segment assignment
Replica group segment assignment is achieved in realtime, if number of servers is a multiple of number of replicas. The partitions get uniformly sprayed across the servers, creating replica groups.
For example, consider we have 6 partitions, 2 replicas, and 4 servers.
r1
r2
As you can see, the set (S0, S2) contains r1 of every partition, and (s1, S3) contains r2 of every partition. The query will only be routed to one of the sets, and not span every server.
If you are are adding/removing servers from an existing table setup, you have to run for segment assignment changes to take effect.
Replica group query routing
Once replica group segment assignment is in effect, the query routing can take advantage of it. For replica group based query routing, set the following in the table config's section, and then restart brokers
Ingestion FAQ
Data processing
What is a good segment size?
While Pinot can work with segments of various sizes, for optimal use of Pinot, you want to get your segments sized in the 100MB to 500MB (un-tarred/uncompressed) range. Please note that having too many (thousands or more) of tiny segments for a single table just creates more overhead in terms of the metadata storage in Zookeeper as well as in the Pinot servers' heap. At the same time, having too few really large (GBs) segments reduces parallelism of query execution, as on the server side, the thread parallelism of query execution is at segment level.
Can multiple Pinot tables consume from the same Kafka topic?
Yes. Each table can be independently configured to consume from any given Kafka topic, regardless of whether there are other tables that are also consuming from the same Kafka topic.
If I add a partition to a Kafka topic, will Pinot automatically ingest data from this partition?
Pinot automatically detects new partitions in Kafka topics. It checks for new partitions whenever RealtimeSegmentValidationManager periodic job runs and starts consumers for new partitions.
You can configure the interval for this job using thecontroller.realtime.segment.validation.frequencyPeriod property in controller configuration.
How do I enable partitioning in Pinot, when using Kafka stream?
Setup partitioner in the Kafka producer:
The partitioning logic in the stream should match the partitioning config in Pinot. Kafka uses murmur2, and the equivalent in Pinot is Murmur function.
Set partitioning config as below using same column used in Kafka
and also set
More details about how partitioner works in Pinot .
How do I store BYTES column in JSON data?
For JSON, you can use hex encoded string to ingest BYTES
How do I flatten my JSON Kafka stream?
See the function which can store a top level json field as a STRING in Pinot.
Then you can use these during query time, to extract fields from the json string.
NOTE
This works well if some of your fields are nested json, but most of your fields are top level json keys. If all of your fields are within a nested JSON key, you will have to store the entire payload as 1 column, which is not ideal.
Support for flattening during ingestion is on the roadmap:
How do I escape Unicode in my Job Spec YAML file?
To use explicit code points, you must double-quote (not single-quote) the string, and escape the code point via "\uHHHH", where HHHH is the four digit hex code for the character. See for more details.
Is there a limit on the maximum length of a string column in Pinot?
By default, Pinot limits the length of a String column to 512 bytes. If you want to overwrite this value, you can set the maxLength attribute in the schema as follows:
When can new events become queryable when getting ingested into a real-time table?
Events are available to queries as soon as they are ingested. This is because events are instantly indexed in memory upon ingestion.
The ingestion of events into the real-time table is not transactional, so replicas of the open segment are not immediately consistent. Pinot trades consistency for availability upon network partitioning (CAP theorem) to provide ultra-low ingestion latencies at high throughput.
However, when the open segment is closed and its in-memory indexes are flushed to persistent storage, all its replicas are guaranteed to be consistent, with the .
How to reset a CONSUMING segment stuck on an offset which has expired from the stream?
This typically happens if
The consumer is lagging a lot
The consumer was down (server down, cluster down), and the stream moved on, resulting in offset not found when consumer comes back up.
In case of Kafka, to recover, set property "auto.offset.reset":"earliest" in the streamConfigs section and reset the CONSUMING segment. See for more details about the config.
You can also also use the "Resume Consumption" endpoint with "resumeFrom" parameter set to "smallest" (or "largest" if you want). Refer to for more details.
Indexing
How to set inverted indexes?
Inverted indexes are set in the tableConfig's tableIndexConfig -> invertedIndexColumns list. For documentation on table config, see . For an example showing how to configure an inverted index, see .
Applying inverted indexes to a table config will generate an inverted index for all new segments. To apply the inverted indexes to all existing segments, see
How to apply an inverted index to existing segments?
Add the columns you wish to index to the tableIndexConfig-> invertedIndexColumns list. To update the table config use the Pinot Swagger API:
Invoke the reload API:
Once you've done that, you can check whether the index has been applied by querying the segment metadata API at . Don't forget to include the names of the column on which you have applied the index.
The output from this API should look something like the following:
Can I retrospectively add an index to any segment?
Not all indexes can be retrospectively applied to existing segments.
If you want to add or change the or adjust you will need to manually re-load any existing segments.
How to create star-tree indexes?
Star-tree indexes are configured in the table config under the tableIndexConfig -> starTreeIndexConfigs (list) and enableDefaultStarTree (boolean). Read more about how to configure star-tree indexes:
The new segments will have star-tree indexes generated after applying the star-tree index configs to the table config. Currently, Pinot does not support adding star-tree indexes to the existing segments.
Handling time in Pinot
How does Pinot’s real-time ingestion handle out-of-order events?
Pinot does not require ordering of event time stamps. Out of order events are still consumed and indexed into the "currently consuming" segment. In a pathological case, if you have a 2 day old event come in "now", it will still be stored in the segment that is open for consumption "now". There is no strict time-based partitioning for segments, but star-indexes and hybrid tables will handle this as appropriate.
See the for more details about how hybrid tables handle this. Specifically, the time-boundary is computed as max(OfflineTIme) - 1 unit of granularity. Pinot does store the min-max time for each segment and uses it for pruning segments, so segments with multiple time intervals may not be perfectly pruned.
When generating star-indexes, the time column will be part of the star-tree so the tree can still be efficiently queried for segments with multiple time intervals.
What is the purpose of a hybrid table not using max(OfflineTime) to determine the time-boundary, and instead using an offset?
This lets you have an old event up come in without building complex offline pipelines that perfectly partition your events by event timestamps. With this offset, even if your offline data pipeline produces segments with a maximum timestamp, Pinot will not use the offline dataset for that last chunk of segments. The expectation is if you process offline the next time-range of data, your data pipeline will include any late events.
Why are segments not strictly time-partitioned?
It might seem odd that segments are not strictly time-partitioned, unlike similar systems such as Apache Druid. This allows real-time ingestion to consume out-of-order events. Even though segments are not strictly time-partitioned, Pinot will still index, prune, and query segments intelligently by time intervals for the performance of hybrid tables and time-filtered data.
When generating offline segments, the segments generated such that segments only contain one time interval and are well partitioned by the time column.
Using "POST /cluster/configs" API on CLUSTER tab in Swagger, with this payload
{
"<taskType>.timeoutMs": "600000",
"<taskType>.numConcurrentTasksPerInstance": "4"
}