Yes.
Thanks for bringing this up Hequn! :-) I think Tuple would not be the best
container to use.
However, in search for alternative, shouldn't Collection / List be a more
suitable solution? Row seems to not fit in the context (as there can be
Rows with elements of different type).
I vaguely recall there was similar JIRA but might not be related to IN
clause. Let me try to dig it up.
--
Rong
On Fri, Sep 28, 2018 at 9:32 AM Hequn Cheng <chenghe...@gmail.com> wrote:
> Hi,
>
> I haven't look into the code. If this is limited by Tuple, would it better
> to implement it with Row?
>
> Best, Hequn
>
> On Fri, Sep 28, 2018 at 9:27 PM Rong Rong <walter...@gmail.com> wrote:
>
>> Hi Henry, Vino.
>>
>> I think IN operator was translated into either a RexSubQuery or a
>> SqlStdOperatorTable.IN operator.
>> I think Vino was referring to the first case.
>> For the second case (I think that's what you are facing here), they are
>> converted into tuples and the maximum we currently have in Flink was
>> Tuple25.java, I was wondering if that was the issue you are facing. You
>> can probably split the IN into many IN combining with OR.
>>
>> --
>> Rong
>>
>> On Fri, Sep 28, 2018 at 2:33 AM vino yang <yanghua1...@gmail.com> wrote:
>>
>>> Hi Henry,
>>>
>>> Maybe the number of elements in your IN clause is out of range? Its
>>> default value is 20, you can modify it with this configuration item:
>>>
>>> *withInSubQueryThreshold(XXX)*
>>>
>>> This API comes from Calcite.
>>>
>>> Thanks, vino.
>>>
>>> 徐涛 <happydexu...@gmail.com> 于2018年9月28日周五 下午4:23写道：
>>>
>>>> Hi,
>>>>
>>>> When I am executing the following SQL in flink 1.6.1, some error
>>>> throws out saying that it has a support issue, but when I reduce the
>>>> number of integers in the “in” sentence, for example,
>>>>
>>>> trackId in (124427150,71648998) , Flink does not complain anything, so
>>>> I wonder is there any length limit in “in” operation?
>>>>
>>>> Thanks a lot.
>>>>
>>>> SELECT
>>>> trackId as id,track_title as description, count(*) as cnt
>>>> FROM
>>>> play
>>>> WHERE
>>>> appName='play.statistics.trace' and
>>>> trackId in
>>>> (124427150,71648998,124493327,524043,27300837,30300481,27300809,124744768,45982512,124526566,124556427,124804208,74302264,119588973,30496269,27300288,124098818,125071530,120918746,124171456,30413034,124888075,125270551,125434224,27300195,45982342,45982468,45982355,65349883,124705962,65349905,124298305,124889583,45982338,20506255,18556415,122161128,27299018,122850375,124862362,45982336,59613202,122991190,124590280,124867563,45982332,124515944,20506257,122572115,92083574)
>>>> GROUP BY
>>>> HOP(started_at_ts, INTERVAL '5' SECOND, INTERVAL '5'
>>>> MINUTE),trackId,track_title;
>>>>
>>>>
>>>>
>>>> FlinkLogicalWindowAggregate(group=[{1, 2}], cnt=[COUNT()])
>>>> FlinkLogicalCalc(expr#0..3=[{inputs}], started_at_ts=[$t2],
>>>> trackId=[$t0], track_title=[$t1])
>>>> FlinkLogicalJoin(condition=[=($0, $3)], joinType=[inner])
>>>> FlinkLogicalCalc(expr#0..4=[{inputs}],
>>>> expr#5=[_UTF-16LE'play.statistics.trace'], expr#6=[=($t0, $t5)],
>>>> trackId=[$t1], track_title=[$t2], started_at_ts=[$t4], $condition=[$t6])
>>>> FlinkLogicalNativeTableScan(table=[[play]])
>>>> FlinkLogicalValues(tuples=[[{ 124427150 }, { 71648998 }, {
>>>> 124493327 }, { 524043 }, { 27300837 }, { 30300481 }, { 27300809 }, {
>>>> 124744768 }, { 45982512 }, { 124526566 }, { 124556427 }, { 124804208 }, {
>>>> 74302264 }, { 119588973 }, { 30496269 }, { 27300288 }, { 124098818 }, {
>>>> 125071530 }, { 120918746 }, { 124171456 }, { 30413034 }, { 124888075 }, {
>>>> 125270551 }, { 125434224 }, { 27300195 }, { 45982342 }, { 45982468 }, {
>>>> 45982355 }, { 65349883 }, { 124705962 }, { 65349905 }, { 124298305 }, {
>>>> 124889583 }, { 45982338 }, { 20506255 }, { 18556415 }, { 122161128 }, {
>>>> 27299018 }, { 122850375 }, { 124862362 }, { 45982336 }, { 59613202 }, {
>>>> 122991190 }, { 124590280 }, { 124867563 }, { 45982332 }, { 124515944 }, {
>>>> 20506257 }, { 122572115 }, { 92083574 }]])
>>>>
>>>> This exception indicates that the query uses an unsupported SQL feature.
>>>> Please check the documentation for the set of currently supported SQL
>>>> features.
>>>> at
>>>> org.apache.flink.table.api.TableEnvironment.runVolcanoPlanner(TableEnvironment.scala:275)
>>>> at
>>>> org.apache.flink.table.api.StreamTableEnvironment.optimize(StreamTableEnvironment.scala:845)
>>>> at
>>>> org.apache.flink.table.api.StreamTableEnvironment.translate(StreamTableEnvironment.scala:892)
>>>> at
>>>> org.apache.flink.table.api.StreamTableEnvironment.writeToSink(StreamTableEnvironment.scala:344)
>>>> at
>>>> org.apache.flink.table.api.TableEnvironment.insertInto(TableEnvironment.scala:786)
>>>> at
>>>> org.apache.flink.table.api.TableEnvironment.sqlUpdate(TableEnvironment.scala:723)
>>>> at
>>>> org.apache.flink.table.api.TableEnvironment.sqlUpdate(TableEnvironment.scala:683)
>>>> at
>>>> com.ximalaya.flink.dsl.application.FlinkApplication$$anonfun$main$5.apply(FlinkApplication.scala:141)
>>>> at
>>>> com.ximalaya.flink.dsl.application.FlinkApplication$$anonfun$main$5.apply(FlinkApplication.scala:139)
>>>> at
>>>> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
>>>> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
>>>> at
>>>> com.ximalaya.flink.dsl.application.FlinkApplication$.main(FlinkApplication.scala:139)
>>>> at
>>>> com.ximalaya.flink.dsl.web.test.DslTestUtils$.executeDslFile(DslTestUtils.scala:69)
>>>> at
>>>> com.ximalaya.flink.dsl.web.test.PlayCountTest$.main(PlayCountTest.scala:5)
>>>> at
>>>> com.ximalaya.flink.dsl.web.test.PlayCountTest.main(PlayCountTest.scala)
>>>>
>>>> Best
>>>> Henry
>>>>
>>>
