SehanRathnayake opened a new issue #8927: Requests with period granularity give different results with Different Segment Granularities when the Origin time component overlaps with DST transition Time URL: https://github.com/apache/incubator-druid/issues/8927 Requests with period granularity give different results with Different Segment Granularities when origin value has time component which overlaps DST transition. ### Affected Version 0.16.0-incubating, ### Description When querying with period granularity type with period P1D with origin value which time is 02:00:00 (which overlaps with DST transition on March 10 ) with America/Los_Angeles timezone give different results when datasource has DAY Segment Granularity vs Month Segment Granularity **Dataset** ` {"timestamp":1552125600000,"type":"March 09, 2019 02:00:00 (am)","amount":10} {"timestamp":1552212000000,"type":"March 10, 2019 03:00:00 (am)","amount":10} {"timestamp":1553500800000,"type":"March 25, 2019 01:00:00 (am)","amount":10} {"timestamp":1554886800000,"type":"April 10, 2019 02:00:00 (am)","amount":10} ` QueryGranularity : THIRTY_MINUTES **Request** ```javascript { "queryType":"groupBy", "granularity":{ "type":"period", "period":"P1D", "timeZone":"America/Los_Angeles", "origin":"2018-01-19T02:00:00.000-08:00" }, "dataSource":{ "type":"union", "dataSources":[ "datasource" ] }, "dimensions":[ "type" ], "aggregations":[ { "type":"doubleSum", "name":"toatalSale", "fieldName":"sum_amount" } ], "intervals":[ "2018-01-21T04:22:26.000+0000/2019-04-30T23:59:59.999+0000" ] } ``` **case 1 : With DAY Segment Granularity** ```javascript [ { "version":"v1", "timestamp":"2019-03-09T02:00:00.000-08:00", "event":{ "toatalSale":10.0, "type":"March 09, 2019 02:00:00 (am)" } }, { "version":"v1", "timestamp":"2019-03-10T03:00:00.000-07:00", "event":{ "toatalSale":10.0, "type":"March 10, 2019 03:00:00 (am)" } }, { "version":"v1", "timestamp":"2019-03-24T02:00:00.000-07:00", "event":{ "toatalSale":10.0, "type":"March 25, 2019 01:00:00 (am)" } }, { "version":"v1", "timestamp":"2019-04-10T02:00:00.000-07:00", "event":{ "toatalSale":10.0, "type":"April 10, 2019 02:00:00 (am)" } } ] ``` **case 2 : Datasource with Month Segment Granularity** ```javascript [ { "version":"v1", "timestamp":"2019-03-09T02:00:00.000-08:00", "event":{ "toatalSale":10.0, "type":"March 09, 2019 02:00:00 (am)" } }, { "version":"v1", "timestamp":"2019-03-10T03:00:00.000-07:00", "event":{ "toatalSale":10.0, "type":"March 10, 2019 03:00:00 (am)" } }, { "version":"v1", "timestamp":"2019-03-24T03:00:00.000-07:00", "event":{ "toatalSale":10.0, "type":"March 25, 2019 01:00:00 (am)" } }, { "version":"v1", "timestamp":"2019-04-10T02:00:00.000-07:00", "event":{ "toatalSale":10.0, "type":"April 10, 2019 02:00:00 (am)" } } ] ``` Here when Querying in the datasource with DAY segment Granularity 3rd bucket has start with 2019-03-24T02:00:00.000-07:00 where when Querying in the datasource with Month segment Granularity 3rd bucket has start with 2019-03-24T03:00:00.000-07:00. Which is inconsistent.
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