[jira] [Created] (FLINK-3939) Prevent distinct aggregates and grouping sets from being translated

Fabian Hueske created FLINK-3939: Summary: Prevent distinct aggregates and grouping sets from being translated Key: FLINK-3939 URL: https://issues.apache.org/jira/browse/FLINK-3939 Project: Flink

Preparing Table API & SQL for Flink 1.1.0

Hi everybody, I'd like to start a discussion about blocking issues and outstanding features of the Table API and SQL for the 1.1.0 release. As you probably know, the Table API was completely reworked and ported to Apache Calcite. Moreover, we added initial support for SQL on batch and streaming ta

[jira] [Created] (FLINK-3938) Yarn tests don't run on the current master

Maximilian Michels created FLINK-3938: - Summary: Yarn tests don't run on the current master Key: FLINK-3938 URL: https://issues.apache.org/jira/browse/FLINK-3938 Project: Flink Issue Type

[jira] [Created] (FLINK-3937) Make flink cli list, savepoint, cancel and stop work on Flink-on-YARN clusters

Sebastian Klemke created FLINK-3937: --- Summary: Make flink cli list, savepoint, cancel and stop work on Flink-on-YARN clusters Key: FLINK-3937 URL: https://issues.apache.org/jira/browse/FLINK-3937 Pr

buffering in operators, implementing statistics

Hi guys, I would like to push forward the work here: https://issues.apache.org/jira/browse/FLINK-2147 Can anyone more familiar with streaming api verify if this could be a mature task. The intention is to summarize data over a window like in the case of StreamGroupedFold. Specifically implement c

[jira] [Created] (FLINK-3936) Add MIN / MAX aggregations function for BOOLEAN types

Fabian Hueske created FLINK-3936: Summary: Add MIN / MAX aggregations function for BOOLEAN types Key: FLINK-3936 URL: https://issues.apache.org/jira/browse/FLINK-3936 Project: Flink Issue Typ

[jira] [Created] (FLINK-3935) Invalid check of key and ordering fields in PartitionNode

Fabian Hueske created FLINK-3935: Summary: Invalid check of key and ordering fields in PartitionNode Key: FLINK-3935 URL: https://issues.apache.org/jira/browse/FLINK-3935 Project: Flink Issue

[jira] [Created] (FLINK-3934) Prevent translation of non-equi joins in DataSetJoinRule

Fabian Hueske created FLINK-3934: Summary: Prevent translation of non-equi joins in DataSetJoinRule Key: FLINK-3934 URL: https://issues.apache.org/jira/browse/FLINK-3934 Project: Flink Issue

[jira] [Created] (FLINK-3933) Add an auto-type-extracting DeserializationSchema

Stephan Ewen created FLINK-3933: --- Summary: Add an auto-type-extracting DeserializationSchema Key: FLINK-3933 URL: https://issues.apache.org/jira/browse/FLINK-3933 Project: Flink Issue Type: Bug

Re: remote debugging

You're welcome ;) On Thu, May 19, 2016 at 11:54 AM, Till Rohrmann wrote: > Thanks Flavio for adding the Eclipse section for remote debugging :-) > > On Tue, May 17, 2016 at 5:55 PM, Flavio Pompermaier > wrote: > > > Done ;) > > > > On Tue, May 17, 2016 at 5:37 PM, Robert Metzger > > wrote: > >

Re: remote debugging

Thanks Flavio for adding the Eclipse section for remote debugging :-) On Tue, May 17, 2016 at 5:55 PM, Flavio Pompermaier wrote: > Done ;) > > On Tue, May 17, 2016 at 5:37 PM, Robert Metzger > wrote: > > > Okay, I gave you permissions. > > > > On Tue, May 17, 2016 at 5:22 PM, Flavio Pompermaier

Re: [QUESTION] the differences between DataStream.join() and DataStream.coGroup()

Thanks for your explain!  I get it.  --From:Fabian Hueske Send Time:2016年5月19日(星期四) 15:21To:dev@flink.apache.org ; 伍翀(云邪) Subject:Re: [QUESTION] the differences between DataStream.join() and DataStream.coGroup() Hi, you are right,

Re: [QUESTION] the differences between DataStream.join() and DataStream.coGroup()

Hi, you are right, at them moment join() looks like syntactic sugar around coGroup(). Internally, it calls wraps a FlatJoinFunction in a CoGroupFunction and calls DataStream.coGroup(). This can be done because CoGroup is more generic and can be used to execute a Join. However, there can be also mo

[QUESTION] the differences between DataStream.join() and DataStream.coGroup()

I have read the source code , and found that the JoinedStreams' implementation code is almost the same with CoGroupedStreams' (internally JoinedStreams' implementation is based on CoGroupedStreams). So why we provide two different interface `DataStream.join()` and `DataStream.coGroup()` which ar