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https://issues.apache.org/jira/browse/FLINK-6075?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16060991#comment-16060991
]
ASF GitHub Bot commented on FLINK-6075:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3889#discussion_r123712536
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/dataset/DataSetSort.scala
---
@@ -136,36 +130,21 @@ class DataSetSort(
}
}
- private def directionToOrder(direction: Direction) = {
- direction match {
- case Direction.ASCENDING | Direction.STRICTLY_ASCENDING =>
Order.ASCENDING
- case Direction.DESCENDING | Direction.STRICTLY_DESCENDING =>
Order.DESCENDING
- case _ => throw new IllegalArgumentException("Unsupported
direction.")
- }
-
- }
-
private val fieldCollations = collations.getFieldCollations.asScala
.map(c => (c.getFieldIndex, directionToOrder(c.getDirection)))
- private val sortFieldsToString = fieldCollations
- .map(col => s"${getRowType.getFieldNames.get(col._1)}
${col._2.getShortName}" ).mkString(", ")
-
- private val offsetToString = s"$offset"
-
- private val fetchToString = if (limitEnd == Long.MaxValue) {
- "unlimited"
- } else {
- s"$limitEnd"
+
+ override def toString: String = {
+ s"Sort(by: ($$sortFieldsToString(collations, getRowType))," +
+ " offset: $offsetToString(offset)," +
+ " fetch: $fetchToString(fetch, offset))"
}
-
- override def toString: String =
- s"Sort(by: ($sortFieldsToString), offset: $offsetToString, fetch:
$fetchToString)"
-
+
+
override def explainTerms(pw: RelWriter) : RelWriter = {
super.explainTerms(pw)
- .item("orderBy", sortFieldsToString)
- .item("offset", offsetToString)
- .item("fetch", fetchToString)
+ .item("orderBy", sortFieldsToString(collations, getRowType))
--- End diff --
Move the implementation to `CommonSort`
> Support Limit/Top(Sort) for Stream SQL
> --------------------------------------
>
> Key: FLINK-6075
> URL: https://issues.apache.org/jira/browse/FLINK-6075
> Project: Flink
> Issue Type: New Feature
> Components: Table API & SQL
> Reporter: radu
> Labels: features
> Attachments: sort.png
>
>
> These will be split in 3 separated JIRA issues. However, the design is the
> same only the processing function differs in terms of the output. Hence, the
> design is the same for all of them.
> Time target: Proc Time
> **SQL targeted query examples:**
> *Sort example*
> Q1)` SELECT a FROM stream1 GROUP BY HOP(proctime, INTERVAL '1' HOUR, INTERVAL
> '3' HOUR) ORDER BY b`
> Comment: window is defined using GROUP BY
> Comment: ASC or DESC keywords can be placed to mark the ordering type
> *Limit example*
> Q2) `SELECT a FROM stream1 WHERE rowtime BETWEEN current_timestamp - INTERVAL
> '1' HOUR AND current_timestamp ORDER BY b LIMIT 10`
> Comment: window is defined using time ranges in the WHERE clause
> Comment: window is row triggered
> *Top example*
> Q3) `SELECT sum(a) OVER (ORDER BY proctime RANGE INTERVAL '1' HOUR PRECEDING
> LIMIT 10) FROM stream1`
> Comment: limit over the contents of the sliding window
> General Comments:
> -All these SQL clauses are supported only over windows (bounded collections
> of data).
> -Each of the 3 operators will be supported with each of the types of
> expressing the windows.
> **Description**
> The 3 operations (limit, top and sort) are similar in behavior as they all
> require a sorted collection of the data on which the logic will be applied
> (i.e., select a subset of the items or the entire sorted set). These
> functions would make sense in the streaming context only in the context of a
> window. Without defining a window the functions could never emit as the sort
> operation would never trigger. If an SQL query will be provided without
> limits an error will be thrown (`SELECT a FROM stream1 TOP 10` -> ERROR).
> Although not targeted by this JIRA, in the case of working based on event
> time order, the retraction mechanisms of windows and the lateness mechanisms
> can be used to deal with out of order events and retraction/updates of
> results.
> **Functionality example**
> We exemplify with the query below for all the 3 types of operators (sorting,
> limit and top). Rowtime indicates when the HOP window will trigger – which
> can be observed in the fact that outputs are generated only at those moments.
> The HOP windows will trigger at every hour (fixed hour) and each event will
> contribute/ be duplicated for 2 consecutive hour intervals. Proctime
> indicates the processing time when a new event arrives in the system. Events
> are of the type (a,b) with the ordering being applied on the b field.
> `SELECT a FROM stream1 HOP(proctime, INTERVAL '1' HOUR, INTERVAL '2' HOUR)
> ORDER BY b (LIMIT 2/ TOP 2 / [ASC/DESC] `)
> ||Rowtime|| Proctime|| Stream1|| Limit 2|| Top 2|| Sort
> [ASC]||
> | |10:00:00 |(aaa, 11) | | |
> |
> | |10:05:00 |(aab, 7) | | | |
> |10-11 |11:00:00 | | aab,aaa |aab,aaa | aab,aaa
> |
> | |11:03:00 |(aac,21) | | | |
>
> |11-12 |12:00:00 | | aab,aaa |aab,aaa | aab,aaa,aac|
> | |12:10:00 |(abb,12) | | | |
>
> | |12:15:00 |(abb,12) | | | |
>
> |12-13 |13:00:00 | | abb,abb | abb,abb |
> abb,abb,aac|
> |...|
> **Implementation option**
> Considering that the SQL operators will be associated with window boundaries,
> the functionality will be implemented within the logic of the window as
> follows.
> * Window assigner – selected based on the type of window used in SQL
> (TUMBLING, SLIDING…)
> * Evictor/ Trigger – time or count evictor based on the definition of the
> window boundaries
> * Apply – window function that sorts data and selects the output to trigger
> (based on LIMIT/TOP parameters). All data will be sorted at once and result
> outputted when the window is triggered
> An alternative implementation can be to use a fold window function to sort
> the elements as they arrive, one at a time followed by a flatMap to filter
> the number of outputs.
> !sort.png!
> **General logic of Join**
> ```
> inputDataStream.window(new [Slide/Tumble][Time/Count]Window())
> //.trigger(new [Time/Count]Trigger()) – use default
> //.evictor(new [Time/Count]Evictor()) – use default
> .apply(SortAndFilter());
> ```
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