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
<mailto: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
<mailto: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 <mailto: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
<mailto: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