[jira] [Resolved] (FLINK-1942) Add configuration options to Gelly-GSA
[ https://issues.apache.org/jira/browse/FLINK-1942?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Vasia Kalavri resolved FLINK-1942. -- Resolution: Fixed Fix Version/s: 0.9 Add configuration options to Gelly-GSA -- Key: FLINK-1942 URL: https://issues.apache.org/jira/browse/FLINK-1942 Project: Flink Issue Type: Improvement Components: Gelly Affects Versions: 0.9 Reporter: Vasia Kalavri Assignee: Andra Lungu Fix For: 0.9 Currently, it is not possible to configure a GSA iteration. Similarly to vertex-centric, we should allow setting the iteration name and degree of parallelism, aggregators, broadcast variables and whether the solution set is kept in unmanaged memory. The docs should be updated accordingly. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Commented] (FLINK-1942) Add configuration options to Gelly-GSA
[ https://issues.apache.org/jira/browse/FLINK-1942?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14547236#comment-14547236 ] ASF GitHub Bot commented on FLINK-1942: --- Github user asfgit closed the pull request at: https://github.com/apache/flink/pull/635 Add configuration options to Gelly-GSA -- Key: FLINK-1942 URL: https://issues.apache.org/jira/browse/FLINK-1942 Project: Flink Issue Type: Improvement Components: Gelly Affects Versions: 0.9 Reporter: Vasia Kalavri Assignee: Andra Lungu Currently, it is not possible to configure a GSA iteration. Similarly to vertex-centric, we should allow setting the iteration name and degree of parallelism, aggregators, broadcast variables and whether the solution set is kept in unmanaged memory. The docs should be updated accordingly. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[GitHub] flink pull request: [FLINK-1942][gelly] GSA Iteration Configuratio...
Github user asfgit closed the pull request at: https://github.com/apache/flink/pull/635 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] flink pull request: [streaming] Fast calculation of medians of win...
GitHub user ggevay opened a pull request: https://github.com/apache/flink/pull/684 [streaming] Fast calculation of medians of windows [WIP] I started working on my Google Summer of Code Project. I decided to start with the fast calculation of medians of windows. The MedianPreReducer keeps track of the median at every window change by keeping the lower and upper halves of the window in two multisets. The updates have logarithmic runtime with the current window size. (Adding an element to or removing an element from the window involves moving at most one of the other elements between the lower and upper halves.) The parameters of WindowedDataStream.median is the same as for the sum, min, max, etc. methods. (But here, the specified field can only be of Double type.) I implemented a few helper classes for accessing the field that is specified by these parameters. I think that the other methods with similar field selection (sum, min, max, etc.) could also be refactored to use these helper classes, so that the code duplication in SumAggregator and ComparableAggregator could be eliminated (the duplication of both the field access logic, and the logic of the byAggregate comparisons). Should I do this refactoring? Currently, the implementation only handles non-grouped data streams, but I plan to create a GroupedMedianPreReducer (hence the [WIP] flag). You can merge this pull request into a Git repository by running: $ git pull https://github.com/ggevay/flink median Alternatively you can review and apply these changes as the patch at: https://github.com/apache/flink/pull/684.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #684 commit 7131289e9f7ab56ec82f12c3a25f146a17354f61 Author: Gabor Gevay gga...@gmail.com Date: 2015-05-17T23:59:31Z [streaming] Fast calculation of medians of windows --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] flink pull request: [Flink-1985] Streaming does not correctly forw...
Github user mbalassi commented on the pull request: https://github.com/apache/flink/pull/682#issuecomment-102773476 Thanks, nice fix. I added one little amend: used `TestStreamEnvironment` instead of local. The former lets you force a given parallelism regardless of the machine. It is not really relevant in this case, but is just a general good practice to always run the environment related tests in parallel. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[jira] [Commented] (FLINK-2023) TypeExtractor does not work for (some) Scala Classes
[ https://issues.apache.org/jira/browse/FLINK-2023?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14547105#comment-14547105 ] Alexander Alexandrov commented on FLINK-2023: - I suggest to have a thin layer which implicitly provides the TypeInformations over the Gelly Java API in Scala (similar to what [~aljoscha] has done with the DataSet Scala API). TypeExtractor does not work for (some) Scala Classes Key: FLINK-2023 URL: https://issues.apache.org/jira/browse/FLINK-2023 Project: Flink Issue Type: Bug Components: Type Serialization System Reporter: Aljoscha Krettek [~vanaepi] discovered some problems while working on the Scala Gelly API where, for example, a Scala MapFunction can not be correctly analyzed by the type extractor. For example, generic types will not be correctly detected. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Resolved] (FLINK-1260) Add custom partitioning to documentation
[ https://issues.apache.org/jira/browse/FLINK-1260?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Robert Metzger resolved FLINK-1260. --- Resolution: Fixed Fix Version/s: 0.9 Assignee: Robert Metzger Resolved as part of http://git-wip-us.apache.org/repos/asf/flink/commit/b335f587 Add custom partitioning to documentation Key: FLINK-1260 URL: https://issues.apache.org/jira/browse/FLINK-1260 Project: Flink Issue Type: Bug Components: Documentation, Java API, Scala API Affects Versions: 0.7.0-incubating Reporter: Fabian Hueske Assignee: Robert Metzger Priority: Minor Fix For: 0.9 The APIs allow to define a custom partitioner to manually fix data skew. This feature is not documented. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[GitHub] flink pull request: [Flink-1985] Streaming does not correctly forw...
Github user rmetzger commented on the pull request: https://github.com/apache/flink/pull/682#issuecomment-102776567 Thank you for the contribution. I would like to wait for some more feedback from other committers before we merge this. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] flink pull request: [Flink-1985] Streaming does not correctly forw...
Github user rmetzger commented on a diff in the pull request:
https://github.com/apache/flink/pull/682#discussion_r30469078
--- Diff:
flink-core/src/main/java/org/apache/flink/api/common/ExecutionConfig.java ---
@@ -543,6 +542,144 @@ public void disableAutoTypeRegistration() {
this.disableAutoTypeRegistration = false;
}
+ @Override
+ public int hashCode() {
+ final int prime = 31;
+ int result = 1;
+ result = prime
+ * result
+ + ((defaultKryoSerializerClasses == null) ? 0
+ :
defaultKryoSerializerClasses.hashCode());
+ result = prime
+ * result
+ + ((defaultKryoSerializers == null) ? 0
+ :
defaultKryoSerializers.hashCode());
+ result = prime * result + (disableAutoTypeRegistration ? 1231 :
1237);
+ result = prime * result
+ + ((executionMode == null) ? 0 :
executionMode.hashCode());
+ result = prime * result + (forceAvro ? 1231 : 1237);
+ result = prime * result + (forceKryo ? 1231 : 1237);
+ result = prime
+ * result
+ + ((globalJobParameters == null) ? 0 :
globalJobParameters
+ .hashCode());
+ result = prime * result + numberOfExecutionRetries;
+ result = prime * result + (objectReuse ? 1231 : 1237);
+ result = prime * result + parallelism;
+ result = prime * result + (printProgressDuringExecution ? 1231
: 1237);
+ result = prime
+ * result
+ + ((registeredKryoTypes == null) ? 0 :
registeredKryoTypes
+ .hashCode());
+ result = prime
+ * result
+ + ((registeredPojoTypes == null) ? 0 :
registeredPojoTypes
+ .hashCode());
+ result = prime
+ * result
+ + ((registeredTypesWithKryoSerializerClasses ==
null) ? 0
+ :
registeredTypesWithKryoSerializerClasses.hashCode());
+ result = prime
+ * result
+ + ((registeredTypesWithKryoSerializers == null)
? 0
+ :
registeredTypesWithKryoSerializers.hashCode());
+ result = prime * result + (useClosureCleaner ? 1231 : 1237);
+ return result;
+ }
+
+ @Override
+ public boolean equals(Object obj) {
+ if (this == obj) {
+ return true;
+ }
+ if (obj == null) {
+ return false;
+ }
+ if (getClass() != obj.getClass()) {
+ return false;
+ }
+ ExecutionConfig other = (ExecutionConfig) obj;
+ if (defaultKryoSerializerClasses == null) {
+ if (other.defaultKryoSerializerClasses != null) {
+ return false;
+ }
+ } else if (!defaultKryoSerializerClasses
+ .equals(other.defaultKryoSerializerClasses)) {
+ return false;
+ }
+ if (defaultKryoSerializers == null) {
+ if (other.defaultKryoSerializers != null) {
+ return false;
+ }
+ } else if
(!defaultKryoSerializers.equals(other.defaultKryoSerializers)) {
+ return false;
+ }
+ if (disableAutoTypeRegistration !=
other.disableAutoTypeRegistration) {
+ return false;
+ }
+ if (executionMode != other.executionMode) {
+ return false;
+ }
+ if (forceAvro != other.forceAvro) {
+ return false;
+ }
+ if (forceKryo != other.forceKryo) {
+ return false;
+ }
+ if (globalJobParameters == null) {
+ if (other.globalJobParameters != null) {
+ return false;
+ }
+ } else if
(!globalJobParameters.equals(other.globalJobParameters)) {
+ return false;
+ }
+ if (numberOfExecutionRetries != other.numberOfExecutionRetries)
{
+
[GitHub] flink pull request: [Flink-1985] Streaming does not correctly forw...
Github user mbalassi commented on the pull request: https://github.com/apache/flink/pull/682#issuecomment-102779406 Ok, I am not pushing until we get some more feedback then. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] flink pull request: [Flink-1985] Streaming does not correctly forw...
Github user mjsax commented on the pull request: https://github.com/apache/flink/pull/682#issuecomment-102780139 Changed LocalStreamEnvironment to TestStreamEnvironment. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[jira] [Commented] (FLINK-1985) Streaming does not correctly forward ExecutionConfig to runtime
[
https://issues.apache.org/jira/browse/FLINK-1985?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14547107#comment-14547107
]
Robert Metzger commented on FLINK-1985:
---
[~mjsax]: The issue is assigned to [~aljoscha]. I'm not 100% sure but I think I
know from an offline discussion with him that he has already a fix for this in
one of his open pull requests.
Lets wait for his comment on this.
I don't see why the variable is unused? The
{{config.isAutoTypeRegistrationDisabled()}} is called in
{{ExecutionEnvironment}}. So there is at least one piece of code which is using
the variable.
Streaming does not correctly forward ExecutionConfig to runtime
---
Key: FLINK-1985
URL: https://issues.apache.org/jira/browse/FLINK-1985
Project: Flink
Issue Type: Bug
Components: Streaming
Affects Versions: 0.9
Reporter: Aljoscha Krettek
Assignee: Aljoscha Krettek
Priority: Blocker
When running streaming jobs you see this log entry:
Environment did not contain an ExecutionConfig - using a default config.
Some parts of the code use an ExecutionConfig at runtime. This will be a
default config without registered serializers and other user settings.
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[jira] [Commented] (FLINK-2031) Missing images in blog posts
[ https://issues.apache.org/jira/browse/FLINK-2031?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14547110#comment-14547110 ] Robert Metzger commented on FLINK-2031: --- A user also reported numerous broken links in the blog posts due to the reorganization of the documentation. I think somebody has to go over all the posts and fix them. Missing images in blog posts Key: FLINK-2031 URL: https://issues.apache.org/jira/browse/FLINK-2031 Project: Flink Issue Type: Bug Components: Project Website Reporter: Fabian Hueske Labels: starter Images are missing in a couple of blog posts after the migration: - Introducing Flink Streaming - Peeking into Flink's Engine Room - Hadoop Compatibility in Flink - maybe others as well -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (FLINK-2031) Missing images in blog posts
[ https://issues.apache.org/jira/browse/FLINK-2031?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Robert Metzger updated FLINK-2031: -- Labels: starter (was: ) Missing images in blog posts Key: FLINK-2031 URL: https://issues.apache.org/jira/browse/FLINK-2031 Project: Flink Issue Type: Bug Components: Project Website Reporter: Fabian Hueske Labels: starter Images are missing in a couple of blog posts after the migration: - Introducing Flink Streaming - Peeking into Flink's Engine Room - Hadoop Compatibility in Flink - maybe others as well -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Commented] (FLINK-1985) Streaming does not correctly forward ExecutionConfig to runtime
[ https://issues.apache.org/jira/browse/FLINK-1985?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14547111#comment-14547111 ] Matthias J. Sax commented on FLINK-1985: Well, the default value of the variable is false and there is no way to set it to true. There is not method enableAutoTypeRegistration(). Streaming does not correctly forward ExecutionConfig to runtime --- Key: FLINK-1985 URL: https://issues.apache.org/jira/browse/FLINK-1985 Project: Flink Issue Type: Bug Components: Streaming Affects Versions: 0.9 Reporter: Aljoscha Krettek Assignee: Aljoscha Krettek Priority: Blocker When running streaming jobs you see this log entry: Environment did not contain an ExecutionConfig - using a default config. Some parts of the code use an ExecutionConfig at runtime. This will be a default config without registered serializers and other user settings. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[GitHub] flink pull request: [Flink-1985] Streaming does not correctly forw...
Github user mjsax commented on a diff in the pull request:
https://github.com/apache/flink/pull/682#discussion_r30469207
--- Diff:
flink-core/src/main/java/org/apache/flink/api/common/ExecutionConfig.java ---
@@ -543,6 +542,144 @@ public void disableAutoTypeRegistration() {
this.disableAutoTypeRegistration = false;
}
+ @Override
+ public int hashCode() {
+ final int prime = 31;
+ int result = 1;
+ result = prime
+ * result
+ + ((defaultKryoSerializerClasses == null) ? 0
+ :
defaultKryoSerializerClasses.hashCode());
+ result = prime
+ * result
+ + ((defaultKryoSerializers == null) ? 0
+ :
defaultKryoSerializers.hashCode());
+ result = prime * result + (disableAutoTypeRegistration ? 1231 :
1237);
+ result = prime * result
+ + ((executionMode == null) ? 0 :
executionMode.hashCode());
+ result = prime * result + (forceAvro ? 1231 : 1237);
+ result = prime * result + (forceKryo ? 1231 : 1237);
+ result = prime
+ * result
+ + ((globalJobParameters == null) ? 0 :
globalJobParameters
+ .hashCode());
+ result = prime * result + numberOfExecutionRetries;
+ result = prime * result + (objectReuse ? 1231 : 1237);
+ result = prime * result + parallelism;
+ result = prime * result + (printProgressDuringExecution ? 1231
: 1237);
+ result = prime
+ * result
+ + ((registeredKryoTypes == null) ? 0 :
registeredKryoTypes
+ .hashCode());
+ result = prime
+ * result
+ + ((registeredPojoTypes == null) ? 0 :
registeredPojoTypes
+ .hashCode());
+ result = prime
+ * result
+ + ((registeredTypesWithKryoSerializerClasses ==
null) ? 0
+ :
registeredTypesWithKryoSerializerClasses.hashCode());
+ result = prime
+ * result
+ + ((registeredTypesWithKryoSerializers == null)
? 0
+ :
registeredTypesWithKryoSerializers.hashCode());
+ result = prime * result + (useClosureCleaner ? 1231 : 1237);
+ return result;
+ }
+
+ @Override
+ public boolean equals(Object obj) {
+ if (this == obj) {
+ return true;
+ }
+ if (obj == null) {
+ return false;
+ }
+ if (getClass() != obj.getClass()) {
+ return false;
+ }
+ ExecutionConfig other = (ExecutionConfig) obj;
+ if (defaultKryoSerializerClasses == null) {
+ if (other.defaultKryoSerializerClasses != null) {
+ return false;
+ }
+ } else if (!defaultKryoSerializerClasses
+ .equals(other.defaultKryoSerializerClasses)) {
+ return false;
+ }
+ if (defaultKryoSerializers == null) {
+ if (other.defaultKryoSerializers != null) {
+ return false;
+ }
+ } else if
(!defaultKryoSerializers.equals(other.defaultKryoSerializers)) {
+ return false;
+ }
+ if (disableAutoTypeRegistration !=
other.disableAutoTypeRegistration) {
+ return false;
+ }
+ if (executionMode != other.executionMode) {
+ return false;
+ }
+ if (forceAvro != other.forceAvro) {
+ return false;
+ }
+ if (forceKryo != other.forceKryo) {
+ return false;
+ }
+ if (globalJobParameters == null) {
+ if (other.globalJobParameters != null) {
+ return false;
+ }
+ } else if
(!globalJobParameters.equals(other.globalJobParameters)) {
+ return false;
+ }
+ if (numberOfExecutionRetries != other.numberOfExecutionRetries)
{
+
[jira] [Comment Edited] (FLINK-1731) Add kMeans clustering algorithm to machine learning library
[
https://issues.apache.org/jira/browse/FLINK-1731?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14547149#comment-14547149
]
Hae Joon Lee edited comment on FLINK-1731 at 5/17/15 12:10 PM:
---
Hi, I am testing K-mean right now.
I faced an error could not find implicit value for parameter
I solved a lot of things except for this one.
* Error:(142, 53) could not find implicit value for parameter op:
breeze.linalg.operators.OpDiv.Impl2[breeze.linalg.Vector[Double],Long,That].map(x
= LabeledVector(x._1, x._2.asBreeze / 1L)).withForwardedFields(_1-id)
{code:title=KMeans.scala|borderStyle=solid}
val finalCentroids = centroids.iterate(numIterations) { currentCentroids =
val newCentroids: DataSet[LabeledVector] = input
.map(new SelectNearestCenterMapper).withBroadcastSet(currentCentroids,
CENTROIDS)
.map(x = (x.label, x.vector, 1L)).withForwardedFields(_1; _2)
.groupBy(x = x._1)
.reduce((p1, p2) = (p1._1, (p1._2.asBreeze + p2._2.asBreeze).fromBreeze,
p1._3 + p2._3)).withForwardedFields(_1)
.map(x = LabeledVector(x._1, x._2.asBreeze :/
x._3)).withForwardedFields(_1-id)
newCentroids
}
{code}
As far as I know, the error could not find implicit value for parameter can
be solved by putting exact import class.
I think the error is from :/ operator, so I put 'import
breeze.linalg.operators._' on import line as well. but it does not work.
Have you ever seen this kind of error before?
was (Author: philjjoon):
Hi, I am testing K-mean right now.
I faced an error could not find implicit value for parameter
I solved a lot of things except for this one.
* Error:(142, 53) could not find implicit value for parameter op:
breeze.linalg.operators.OpDiv.Impl2[breeze.linalg.Vector[Double],Long,That].map(x
= LabeledVector(x._1, x._2.asBreeze / 1L)).withForwardedFields(_1-id)
{code:title=KMeans.scala|borderStyle=solid}
val finalCentroids = centroids.iterate(numIterations) { currentCentroids =
val newCentroids: DataSet[LabeledVector] = input
.map(new SelectNearestCenterMapper).withBroadcastSet(currentCentroids,
CENTROIDS)
.map(x = (x.label, x.vector, 1L)).withForwardedFields(_1; _2)
.groupBy(x = x._1)
.reduce((p1, p2) = (p1._1, (p1._2.asBreeze + p2._2.asBreeze).fromBreeze,
p1._3 + p2._3)).withForwardedFields(_1)
.map(x = LabeledVector(x._1, x._2.asBreeze :/
x._3)).withForwardedFields(_1-id)
newCentroids
}
{code}
As far as I know, the error could not find implicit value for parameter can
be solved by putting exact import class.
I put 'import breeze.linalg.operators._' on import line as well.
but it does not work.
Have you ever seen this kind of error before?
Add kMeans clustering algorithm to machine learning library
---
Key: FLINK-1731
URL: https://issues.apache.org/jira/browse/FLINK-1731
Project: Flink
Issue Type: New Feature
Components: Machine Learning Library
Reporter: Till Rohrmann
Assignee: Peter Schrott
Labels: ML
The Flink repository already contains a kMeans implementation but it is not
yet ported to the machine learning library. I assume that only the used data
types have to be adapted and then it can be more or less directly moved to
flink-ml.
The kMeans++ [1] and the kMeans|| [2] algorithm constitute a better
implementation because the improve the initial seeding phase to achieve near
optimal clustering. It might be worthwhile to implement kMeans||.
Resources:
[1] http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf
[2] http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf
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[jira] [Commented] (FLINK-1731) Add kMeans clustering algorithm to machine learning library
[
https://issues.apache.org/jira/browse/FLINK-1731?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14547149#comment-14547149
]
Hae Joon Lee commented on FLINK-1731:
-
Hi, I am testing K-mean right now.
I faced an error could not find implicit value for parameter
I solved a lot of things except for this one.
* Error:(142, 53) could not find implicit value for parameter op:
breeze.linalg.operators.OpDiv.Impl2[breeze.linalg.Vector[Double],Long,That].map(x
= LabeledVector(x._1, x._2.asBreeze / 1L)).withForwardedFields(_1-id)
{code:title=KMeans.scala|borderStyle=solid}
val finalCentroids = centroids.iterate(numIterations) { currentCentroids =
val newCentroids: DataSet[LabeledVector] = input
.map(new SelectNearestCenterMapper).withBroadcastSet(currentCentroids,
CENTROIDS)
.map(x = (x.label, x.vector, 1L)).withForwardedFields(_1; _2)
.groupBy(x = x._1)
.reduce((p1, p2) = (p1._1, (p1._2.asBreeze + p2._2.asBreeze).fromBreeze,
p1._3 + p2._3)).withForwardedFields(_1)
.map(x = LabeledVector(x._1, x._2.asBreeze :/
x._3)).withForwardedFields(_1-id)
newCentroids
}
{code}
As far as I know, the error could not find implicit value for parameter can
be solved by putting exact import class.
I put 'import breeze.linalg.operators._' on import line as well.
but it does not work.
Have you ever seen this kind of error before?
Add kMeans clustering algorithm to machine learning library
---
Key: FLINK-1731
URL: https://issues.apache.org/jira/browse/FLINK-1731
Project: Flink
Issue Type: New Feature
Components: Machine Learning Library
Reporter: Till Rohrmann
Assignee: Peter Schrott
Labels: ML
The Flink repository already contains a kMeans implementation but it is not
yet ported to the machine learning library. I assume that only the used data
types have to be adapted and then it can be more or less directly moved to
flink-ml.
The kMeans++ [1] and the kMeans|| [2] algorithm constitute a better
implementation because the improve the initial seeding phase to achieve near
optimal clustering. It might be worthwhile to implement kMeans||.
Resources:
[1] http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf
[2] http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf
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[jira] [Created] (FLINK-2031) Missing images in blog posts
Fabian Hueske created FLINK-2031: Summary: Missing images in blog posts Key: FLINK-2031 URL: https://issues.apache.org/jira/browse/FLINK-2031 Project: Flink Issue Type: Bug Components: Project Website Reporter: Fabian Hueske Images are missing in a couple of blog posts after the migration: - Introducing Flink Streaming - Peeking into Flink's Engine Room - Hadoop Compatibility in Flink - maybe others as well -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Commented] (FLINK-2023) TypeExtractor does not work for (some) Scala Classes
[ https://issues.apache.org/jira/browse/FLINK-2023?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14547064#comment-14547064 ] Aljoscha Krettek commented on FLINK-2023: - Yes, this is what I observed as well. Unfortunately this is quite bad for things like the Scala Gelli API on which [~vanaepi] is working. TypeExtractor does not work for (some) Scala Classes Key: FLINK-2023 URL: https://issues.apache.org/jira/browse/FLINK-2023 Project: Flink Issue Type: Bug Components: Type Serialization System Reporter: Aljoscha Krettek [~vanaepi] discovered some problems while working on the Scala Gelly API where, for example, a Scala MapFunction can not be correctly analyzed by the type extractor. For example, generic types will not be correctly detected. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Commented] (FLINK-1985) Streaming does not correctly forward ExecutionConfig to runtime
[ https://issues.apache.org/jira/browse/FLINK-1985?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14547175#comment-14547175 ] Aljoscha Krettek commented on FLINK-1985: - [~rmetzger] yes, I have a fix for this in my open pull request. But we can also merge matthias' work since it contains also a Unit test. Streaming does not correctly forward ExecutionConfig to runtime --- Key: FLINK-1985 URL: https://issues.apache.org/jira/browse/FLINK-1985 Project: Flink Issue Type: Bug Components: Streaming Affects Versions: 0.9 Reporter: Aljoscha Krettek Assignee: Aljoscha Krettek Priority: Blocker When running streaming jobs you see this log entry: Environment did not contain an ExecutionConfig - using a default config. Some parts of the code use an ExecutionConfig at runtime. This will be a default config without registered serializers and other user settings. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
