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ASF GitHub Bot commented on FLINK-1297: --------------------------------------- Github user rmetzger commented on a diff in the pull request: https://github.com/apache/flink/pull/605#discussion_r28593066 --- Diff: flink-core/pom.xml --- @@ -63,6 +63,19 @@ under the License. <artifactId>guava</artifactId> <version>${guava.version}</version> </dependency> + + <dependency> + <groupId>com.clearspring.analytics</groupId> + <artifactId>stream</artifactId> + <version>2.7.0</version> + <exclusions> + <exclusion> + <groupId>it.unimi.dsi</groupId> + <artifactId>fastutil</artifactId> --- End diff -- This is an exclusion of fastutil ;) > Add support for tracking statistics of intermediate results > ----------------------------------------------------------- > > Key: FLINK-1297 > URL: https://issues.apache.org/jira/browse/FLINK-1297 > Project: Flink > Issue Type: Improvement > Components: Distributed Runtime > Reporter: Alexander Alexandrov > Assignee: Alexander Alexandrov > Fix For: 0.9 > > Original Estimate: 1,008h > Remaining Estimate: 1,008h > > One of the major problems related to the optimizer at the moment is the lack > of proper statistics. > With the introduction of staged execution, it is possible to instrument the > runtime code with a statistics facility that collects the required > information for optimizing the next execution stage. > I would therefore like to contribute code that can be used to gather basic > statistics for the (intermediate) result of dataflows (e.g. min, max, count, > count distinct) and make them available to the job manager. > Before I start, I would like to hear some feedback form the other users. > In particular, to handle skew (e.g. on grouping) it might be good to have > some sort of detailed sketch about the key distribution of an intermediate > result. I am not sure whether a simple histogram is the most effective way to > go. Maybe somebody would propose another lightweight sketch that provides > better accuracy. -- This message was sent by Atlassian JIRA (v6.3.4#6332)