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Fri, 25 May 2018 08:15:00 +0000 (UTC) Date: Fri, 25 May 2018 08:15:00 +0000 (UTC) From: "Sergey Nuyanzin (JIRA)" To: issues@flink.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Comment Edited] (FLINK-8650) Add tests and documentation for WINDOW clause MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 7bit X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 [ https://issues.apache.org/jira/browse/FLINK-8650?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16490391#comment-16490391 ] Sergey Nuyanzin edited comment on FLINK-8650 at 5/25/18 8:14 AM: ----------------------------------------------------------------- Hello [~twalthr] I would take this issue if you do not mind a question for clarification: am I right that a good point to start is _org.apache.flink.table.runtime.stream.sql.OverWindowITCase_ and check the same queries with the same data but with window clause as you mentioned e.g. now in _org.apache.flink.table.runtime.stream.sql.OverWindowITCase#testProcTimeBoundedPartitionedRowsOver_ there is {code:sql} SELECT a, SUM(c) OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW), MIN(c) OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) FROM MyTable {code} which could be checked against {code:sql} SELECT a, SUM(c) OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW), MIN(c) OVER w FROM MyTable WINDOW w AS (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) {code} {code:sql} SELECT a, SUM(c) OVER w, MIN(c) OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) FROM MyTable WINDOW w AS (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) {code} {code:sql} SELECT a, SUM(c) OVER w, MIN(c) OVER w FROM MyTable WINDOW w AS (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) {code} I guess one thing is it will be nice to do it not manually via copy paste but in a more intelligent approach was (Author: sergey nuyanzin): Hello [~twalthr] I would take this issue if you do not mind a question for clarification: am I right that a good point to start is _org.apache.flink.table.runtime.stream.sql.OverWindowITCase_ and check the same queries with the same data but with window clause as you mentioned e.g. now in _org.apache.flink.table.runtime.stream.sql.OverWindowITCase#testProcTimeBoundedPartitionedRowsOver_ there is {code:sql} SELECT a, SUM(c) OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW), MIN(c) OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) FROM MyTable {code} which could be checked against {code:sql} SELECT a, SUM(c) OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW), MIN(c) OVER w FROM MyTable WINDOW w AS OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) {code} {code:sql} SELECT a, SUM(c) OVER w, MIN(c) OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) FROM MyTable WINDOW w AS OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) {code} {code:sql} SELECT a, SUM(c) OVER w, MIN(c) OVER w FROM MyTable WINDOW w AS OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) {code} I guess one thing is it will be nice to do it not manually via copy paste but in a more intelligent approach > Add tests and documentation for WINDOW clause > --------------------------------------------- > > Key: FLINK-8650 > URL: https://issues.apache.org/jira/browse/FLINK-8650 > Project: Flink > Issue Type: Improvement > Components: Table API & SQL > Reporter: Timo Walther > Assignee: Sergey Nuyanzin > Priority: Major > > We support queries with a {{WINDOW}} clause like: > {code} > SELECT a, SUM(c) OVER w, MIN(c) OVER w FROM MyTable WINDOW w AS (PARTITION BY a ORDER BY proctime ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) > {code} > But this is neither documented nor tested. -- This message was sent by Atlassian JIRA (v7.6.3#76005)