Query Response Format

Standard-SQL response

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": {}
}

Response Field	Description
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	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	This along with numEntriesScannedInPostFilter 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 start-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

Response Field

Description

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

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

This along with numEntriesScannedInPostFilter 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 start-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

PQL response

Note

PQL endpoint is deprecated, and will soon be removed. The standard sql endpoint is the recommended endpoint.

The response received from PQL endpoint is different depending on the type of the query.

curl -X POST \
  -d '{"pql":"select * from flights limit 3"}' \
  http://localhost:8099/query


{
 "selectionResults":{
    "columns":[
       "Cancelled",
       "Carrier",
       "DaysSinceEpoch",
       "Delayed",
       "Dest",
       "DivAirports",
       "Diverted",
       "Month",
       "Origin",
       "Year"
    ],
    "results":[
       [
          "0",
          "AA",
          "16130",
          "0",
          "SFO",
          [],
          "0",
          "3",
          "LAX",
          "2014"
       ],
       [
          "0",
          "AA",
          "16130",
          "0",
          "LAX",
          [],
          "0",
          "3",
          "SFO",
          "2014"
       ],
       [
          "0",
          "AA",
          "16130",
          "0",
          "SFO",
          [],
          "0",
          "3",
          "LAX",
          "2014"
       ]
    ]
 },
 "traceInfo":{},
 "numDocsScanned":3,
 "aggregationResults":[],
 "timeUsedMs":10,
 "segmentStatistics":[],
 "exceptions":[],
 "totalDocs":102
}

curl -X POST \
  -d '{"pql":"select count(*) from flights"}' \
  http://localhost:8099/query


{
 "traceInfo":{},
 "numDocsScanned":17,
 "aggregationResults":[
    {
       "function":"count_star",
       "value":"17"
    }
 ],
 "timeUsedMs":27,
 "segmentStatistics":[],
 "exceptions":[],
 "totalDocs":17
}

curl -X POST \
  -d '{"pql":"select count(*) from flights group by Carrier"}' \
  http://localhost:8099/query


{
 "traceInfo":{},
 "numDocsScanned":23,
 "aggregationResults":[
    {
       "groupByResult":[
          {
             "value":"10",
             "group":["AA"]
          },
          {
             "value":"9",
             "group":["VX"]
          },
          {
             "value":"4",
             "group":["WN"]
          }
       ],
       "function":"count_star",
       "groupByColumns":["Carrier"]
    }
 ],
 "timeUsedMs":47,
 "segmentStatistics":[],
 "exceptions":[],
 "totalDocs":23
}

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Last updated 1 year ago