Pinot can be queried via a broker endpoint as follows. This example assumes broker is running on localhost:8099
The Pinot REST API can be accessed by invoking POST operation with a JSON body containing the parameter sql to the /query/sql endpoint on a broker.
When TLS/SSL is not enabled:
$ curl -H "Content-Type: application/json" -X POST \
-d '{"sql":"select foo, count(*) from myTable group by foo limit 100"}' \
http://localhost:8099/query/sqlWhen TLS/SSL is enabled:
$ curl -k -H "Content-Type: application/json" -X POST \
-d '{"sql":"select foo, count(*) from myTable group by foo limit 100"}' \
https://localhost:8099/query/sqlIf the SQL statement contains ", in the JSON body, it needs to be replaced by '"'"', for example:
$ curl -H "Content-Type: application/json" -X POST \
-d '{"sql":"select foo, count(*) from myTable where foo='"'"'abc'"'"' limit 100"}' \
http://localhost:8099/query/sqlUse Query Console to run ad hoc queries. Access the Query Console by entering the <controller host>:<controller port> in your browser.
You can also query using the pinot-admin scripts. Make sure you follow instructions in Getting Pinot to get Pinot locally, and then
cd incubator-pinot/pinot-tools/target/pinot-tools-pkg
bin/pinot-admin.sh PostQuery \
-queryType sql \
-brokerPort 8000 \
-query "select count(*) from baseballStats"
2020/03/04 12:46:33.459 INFO [PostQueryCommand] [main] Executing command: PostQuery -brokerHost localhost -brokerPort 8000 -queryType sql -query select count(*) from baseballStats
2020/03/04 12:46:33.854 INFO [PostQueryCommand] [main] Result: {"resultTable":{"dataSchema":{"columnDataTypes":["LONG"],"columnNames":["count(*)"]},"rows":[[97889]]},"exceptions":[],"numServersQueried":1,"numServersResponded":1,"numSegmentsQueried":1,"numSegmentsProcessed":1,"numSegmentsMatched":1,"numConsumingSegmentsQueried":0,"numDocsScanned":97889,"numEntriesScannedInFilter":0,"numEntriesScannedPostFilter":0,"numGroupsLimitReached":false,"totalDocs":97889,"timeUsedMs":185,"segmentStatistics":[],"traceInfo":{},"minConsumingFreshnessTimeMs":0}Response is returned in a SQL-like tabular structure. Note, this is the response returned from the standard-SQL endpoint. For PQL endpoint response, skip to PQL endpoint response
$ curl -H "Content-Type: application/json" -X POST \
-d '{"sql":"SELECT moo, bar, foo FROM myTable ORDER BY foo DESC"}' \
http://localhost:8099/query/sql
{
"exceptions": [],
"minConsumingFreshnessTimeMs": 0,
"numConsumingSegmentsQueried": 0,
"numDocsScanned": 6,
"numEntriesScannedInFilter": 0,
"numEntriesScannedPostFilter": 18,
"numGroupsLimitReached": false,
"numSegmentsMatched": 2,
"numSegmentsProcessed": 2,
"numSegmentsQueried": 2,
"numServersQueried": 1,
"numServersResponded": 1,
"resultTable": {
"dataSchema": {
"columnDataTypes": [
"LONG",
"INT",
"STRING"
],
"columnNames": [
"moo",
"bar",
"foo"
]
},
"rows": [
[
40015,
2019,
"xyz"
],
[
1002,
2001,
"pqr"
],
[
20555,
1988,
"pqr"
],
[
203,
2010,
"pqr"
],
[
500,
2008,
"abc"
],
[
60,
2003,
"abc"
]
]
},
"segmentStatistics": [],
"timeUsedMs": 4,
"totalDocs": 6,
"traceInfo": {}
}$ curl -X POST \
-d '{"sql":"SELECT SUM(moo), MAX(bar), COUNT(*) FROM myTable"}' \
localhost:8099/query/sql -H "Content-Type: application/json"
{
"exceptions": [],
"minConsumingFreshnessTimeMs": 0,
"numConsumingSegmentsQueried": 0,
"numDocsScanned": 6,
"numEntriesScannedInFilter": 0,
"numEntriesScannedPostFilter": 12,
"numGroupsLimitReached": false,
"numSegmentsMatched": 2,
"numSegmentsProcessed": 2,
"numSegmentsQueried": 2,
"numServersQueried": 1,
"numServersResponded": 1,
"resultTable": {
"dataSchema": {
"columnDataTypes": [
"DOUBLE",
"DOUBLE",
"LONG"
],
"columnNames": [
"sum(moo)",
"max(bar)",
"count(*)"
]
},
"rows": [
[
62335,
2019.0,
6
]
]
},
"segmentStatistics": [],
"timeUsedMs": 87,
"totalDocs": 6,
"traceInfo": {}
}$ curl -X POST \
-d '{"sql":"SELECT SUM(moo), MAX(bar) FROM myTable GROUP BY foo ORDER BY foo"}' \
localhost:8099/query/sql -H "Content-Type: application/json"
{
"exceptions": [],
"minConsumingFreshnessTimeMs": 0,
"numConsumingSegmentsQueried": 0,
"numDocsScanned": 6,
"numEntriesScannedInFilter": 0,
"numEntriesScannedPostFilter": 18,
"numGroupsLimitReached": false,
"numSegmentsMatched": 2,
"numSegmentsProcessed": 2,
"numSegmentsQueried": 2,
"numServersQueried": 1,
"numServersResponded": 1,
"resultTable": {
"dataSchema": {
"columnDataTypes": [
"STRING",
"DOUBLE",
"DOUBLE"
],
"columnNames": [
"foo",
"sum(moo)",
"max(bar)"
]
},
"rows": [
[
"abc",
560.0,
2008.0
],
[
"pqr",
21760.0,
2010.0
],
[
"xyz",
40015.0,
2019.0
]
]
},
"segmentStatistics": [],
"timeUsedMs": 15,
"totalDocs": 6,
"traceInfo": {}
}resultTable
This contains everything needed to process the response
resultTable.dataSchema
This describes schema of the response (columnNames and their dataTypes)
resultTable.dataSchema.columnNames
columnNames in the response.
resultTable.dataSchema.columnDataTypes
DataTypes for each column
resultTable.rows
Actual content with values. This is an array of arrays. number of rows depends on the limit value in the query. The number of columns in each row is equal to the length of (resultTable.dataSchema.columnNames)
timeUsedms
Total time taken as seen by the broker before sending the response back to the client
totalDocs
This is number of documents/records in the table
numServersQueried
represents the number of servers queried by the broker (note that this may be less than the total number of servers since broker can apply some optimizations to minimize the number of servers)
numServersResponded
This should be equal to the numServersQueried. If this is not the same, then one of more servers might have timed out. If numServersQueried != numServersResponded the results can be considered partial and clients can retry the query with exponential back off.
numSegmentsQueried
Total number of segmentsQueried for this query. it may be less than the total number of segments since broker can apply optimizations.
numSegmentsMatched
This is the number of segments processed with at least one document matched query response. In general numSegmentsQueried <= numSegmentsProcessed <= numSegmentsMatched.
numSegmentsProcessed
Number of segment operators used to process segments. This is indicates the effectiveness of the pruning logic.
numDocScanned
The number of docs/records that were selected after filter phase.
numEntriesScannedInFilter
The number of entries scanned in the filtering phase of query execution.
It could be larger than the total scanned doc count because of multiple filtering predicate and/or multi-value entries.
It can also be smaller than the total scanned doc count if indexing is used for filtering.
This along with numEntriesScannedInPostFilter should give an idea on where most of the time is spent during query processing. If this is high, enabling indexing for columns in tableConfig can be one way to bring it down.
numEntriesScannedPostFilter
The number of entries scanned after the filtering phase of query execution, ie. aggregation and/or group-by phases. This is equivalent to numDocScanned * number of projected columns.
This along with numEntriesScannedInFilter should give an idea on where most of the time is spent during query processing.
A high number for this means the selectivity is low (i.e. pinot needs to scan a lot of records to answer the query). If this is high, adding regular inverted/bitmap index will not help. However, consider using star-tree index.
numGroupsLimitReached
If the query has group by clause and top K, pinot drops new entries after the numGroupsLimit is reached. If this boolean is set to true then the query result may not be accurate. Note that the default value for numGroupsLimit is 100k and should be sufficient for most use cases.
exceptions
Will contain the stack trace if there is any exception processing the query.
segmentStatistics
N/A
traceInfo
If trace is enabled (can be enabled for each query), this will contain the timing for each stage and each segment. Advanced feature and intended for dev/debugging purposes
Note
Pinot Query Language (PQL) endpoint has been deprecated and removed. Use the sql endpoint.