[jira] [Commented] (SPARK-25985) Verify the SPARK-24613 Cache with UDF could not be matched with subsequent dependent caches
[ https://issues.apache.org/jira/browse/SPARK-25985?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17109201#comment-17109201 ] Nick Afshartous commented on SPARK-25985: - [~smilegator] Can you please comment if this task is still relevant. If so I'd like to look into it if you could please elaborate on "works well" in the description. > Verify the SPARK-24613 Cache with UDF could not be matched with subsequent > dependent caches > --- > > Key: SPARK-25985 > URL: https://issues.apache.org/jira/browse/SPARK-25985 > Project: Spark > Issue Type: Sub-task > Components: SQL, Tests >Affects Versions: 3.0.0 >Reporter: Xiao Li >Priority: Major > Labels: starter > > Verify whether recacheByCondition works well when the cache data is with UDF. > This is a follow-up of https://github.com/apache/spark/pull/21602 -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17104661#comment-17104661 ] Nick Afshartous commented on SPARK-27249: - [~enrush] Hi Everett, can you please chime in on the thread in the PR. There's a question about whether or not the need is covered by existing API's. > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.1.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Comment Edited] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17086029#comment-17086029 ] Nick Afshartous edited comment on SPARK-27249 at 4/17/20, 7:54 PM: --- [~enrush] Hi Everett, Using the {{Iterator}} approach would seem to deviate from the existing {{Transformer}} contract. More specifically, the {{transform}} function should output a new {{DataFrame}} object. What I would propose is adding a new function {{Transformer.compose}} to allow the composition of {{Transformers}}. {code} def compose(other: Transformer): Transformer = { new Transformer { override def transform(dataset: Dataset[_]): DataFrame = { other.transform(this.transform(dataset)); } ... {code} Then one could {{compose}} {{Transformers}} which effectively would enable multi-column transformations. {code} val dataFrame = ... val transformers = List(transformer1, transformer2, transformer3) val multiColumnTransformer = transformers.reduce((x, y) => x.compose(y)) multiColumnTransformer.transform(dataFrame) {code} I'd be happy to submit a PR if this meets your requirments. was (Author: nafshartous): [~enrush] Hi Everett, Using the {{Iterator}} approach would seem to deviate from the existing {{Transformer}} contract. More specifically, the {{transform}} function should output a new {{DataFrame}} object. What I would propose is adding a new function {{Transformer.compose}} to allow the composition of {{Transformers}}. {code} def compose(other: Transformer): Transformer = { new Transformer { override def transform(dataset: Dataset[_]): DataFrame = { other.transform(this.transform(dataset)); } ... {code} Then one could {{compose}} {{Transformers}} which effectively would enable multi-column transformations. {code} val dataFrame = ... val transformers = List(transformer1, transformer2, transformer3) val multiColumnTransformer = transformers.reduce((x, y) => x.compose(y)) multiColumnTransformer.transform(dataFrame) {code} I'd be happy to submit a PR if this meets your requirments. > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.1.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17086029#comment-17086029 ] Nick Afshartous commented on SPARK-27249: - [~enrush] Hi Everett, Using the {{Iterator}} approach would seem to deviate from the existing {{Transformer}} contract. More specifically, the {{transform}} function should output a new {{DataFrame}} object. What I would propose is adding a new function {{Transformer.compose}} to allow the composition of {{Transformers}}. {code} def compose(other: Transformer): Transformer = { new Transformer { override def transform(dataset: Dataset[_]): DataFrame = { other.transform(this.transform(dataset)); } ... {code} Then one could {{compose}} {{Transformers}} which effectively would enable multi-column transformations. {code} val dataFrame = ... val transformers = List(transformer1, transformer2, transformer3) val multiColumnTransformer = transformers.reduce((x, y) => x.compose(y)) multiColumnTransformer.transform(dataFrame) {code} I'd be happy to submit a PR if this meets your requirments. > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.1.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17078751#comment-17078751 ] Nick Afshartous commented on SPARK-27249: - [~enrush] Hi Everett, checking back on my question in the last comment. > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.1.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Comment Edited] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17018329#comment-17018329 ] Nick Afshartous edited comment on SPARK-27249 at 1/17/20 9:29 PM: -- [~enrush] Hi Everett, The {{Dataset}} API has an experimental function {{mapPartitions}} for transforming {{Datasets}}. Does this satisfy your requirements ? https://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.sql.Dataset was (Author: nafshartous): [~enrush] Hi Everett, The {{Dataset}} API has an experimental function {{mapPartitions}} for transforming {{Dataset}}s. Does this satisfy your requirements ? https://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.sql.Dataset > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.0.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17018329#comment-17018329 ] Nick Afshartous commented on SPARK-27249: - [~enrush] Hi Everett, The {{Dataset}} API has an experimental function {{mapPartitions}} for transforming {{Dataset}} . Does this satisfy your requirements ? https://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.sql.Dataset > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.0.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Comment Edited] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17018329#comment-17018329 ] Nick Afshartous edited comment on SPARK-27249 at 1/17/20 9:28 PM: -- [~enrush] Hi Everett, The {{Dataset}} API has an experimental function {{mapPartitions}} for transforming {{Dataset}}s. Does this satisfy your requirements ? https://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.sql.Dataset was (Author: nafshartous): [~enrush] Hi Everett, The {{Dataset}} API has an experimental function {{mapPartitions}} for transforming {{Dataset}} . Does this satisfy your requirements ? https://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.sql.Dataset > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.0.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Nick Afshartous updated SPARK-27249: Attachment: Screen Shot 2020-01-17 at 4.20.57 PM.png > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.0.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17018105#comment-17018105 ] Nick Afshartous commented on SPARK-27249: - Thanks Everett, and can someone with permission assign this ticket to me. > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.0.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Comment Edited] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17010756#comment-17010756 ] Nick Afshartous edited comment on SPARK-27249 at 1/9/20 7:49 PM: - I could try and look into this. Could someone validate that this feature is still needed ? [~enrush] It would also be helpful if you could provide a code example illustrating how the {{PartitionTransformer}} would be used. was (Author: nafshartous): I could try and look into this. Could someone validate that this feature is still needed ? > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.0.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17010756#comment-17010756 ] Nick Afshartous commented on SPARK-27249: - I could try and look into this. Could someone validate that this feature is still needed ? > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.0.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19767) API Doc pages for Streaming with Kafka 0.10 not current
[ https://issues.apache.org/jira/browse/SPARK-19767?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16410334#comment-16410334 ] Nick Afshartous commented on SPARK-19767: - Running the full doc build using {{jekyll build}} I get the error {code:java} OSError: [Errno 13] Permission denied: '/usr/lib64/python2.7/site-packages/yaml' {code} Can someone advise. > API Doc pages for Streaming with Kafka 0.10 not current > --- > > Key: SPARK-19767 > URL: https://issues.apache.org/jira/browse/SPARK-19767 > Project: Spark > Issue Type: Bug > Components: DStreams >Affects Versions: 2.1.0 >Reporter: Nick Afshartous >Priority: Minor > > The API docs linked from the Spark Kafka 0.10 Integration page are not > current. For instance, on the page >https://spark.apache.org/docs/latest/streaming-kafka-0-10-integration.html > the code examples show the new API (i.e. class ConsumerStrategies). However, > following the links > API Docs --> (Scala | Java) > lead to API pages that do not have class ConsumerStrategies) . The API doc > package names also have {code}streaming.kafka{code} as opposed to > {code}streaming.kafka10{code} > as in the code examples on streaming-kafka-0-10-integration.html. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19767) API Doc pages for Streaming with Kafka 0.10 not current
[ https://issues.apache.org/jira/browse/SPARK-19767?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16403702#comment-16403702 ] Nick Afshartous commented on SPARK-19767: - Sounds good [~c...@koeninger.org]. I'll close the current PR and submit a new one. > API Doc pages for Streaming with Kafka 0.10 not current > --- > > Key: SPARK-19767 > URL: https://issues.apache.org/jira/browse/SPARK-19767 > Project: Spark > Issue Type: Bug > Components: DStreams >Affects Versions: 2.1.0 >Reporter: Nick Afshartous >Priority: Minor > > The API docs linked from the Spark Kafka 0.10 Integration page are not > current. For instance, on the page >https://spark.apache.org/docs/latest/streaming-kafka-0-10-integration.html > the code examples show the new API (i.e. class ConsumerStrategies). However, > following the links > API Docs --> (Scala | Java) > lead to API pages that do not have class ConsumerStrategies) . The API doc > package names also have {code}streaming.kafka{code} as opposed to > {code}streaming.kafka10{code} > as in the code examples on streaming-kafka-0-10-integration.html. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19767) API Doc pages for Streaming with Kafka 0.10 not current
[ https://issues.apache.org/jira/browse/SPARK-19767?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15900216#comment-15900216 ] Nick Afshartous commented on SPARK-19767: - Missed that one, thanks. > API Doc pages for Streaming with Kafka 0.10 not current > --- > > Key: SPARK-19767 > URL: https://issues.apache.org/jira/browse/SPARK-19767 > Project: Spark > Issue Type: Bug > Components: Structured Streaming >Affects Versions: 2.1.0 >Reporter: Nick Afshartous >Priority: Minor > > The API docs linked from the Spark Kafka 0.10 Integration page are not > current. For instance, on the page >https://spark.apache.org/docs/latest/streaming-kafka-0-10-integration.html > the code examples show the new API (i.e. class ConsumerStrategies). However, > following the links > API Docs --> (Scala | Java) > lead to API pages that do not have class ConsumerStrategies) . The API doc > package names also have {code}streaming.kafka{code} as opposed to > {code}streaming.kafka10{code} > as in the code examples on streaming-kafka-0-10-integration.html. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19767) API Doc pages for Streaming with Kafka 0.10 not current
[ https://issues.apache.org/jira/browse/SPARK-19767?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15900184#comment-15900184 ] Nick Afshartous commented on SPARK-19767: - Yes, I completed the steps in the Prerequisites section of https://github.com/apache/spark/blob/master/docs/README.md and got the same error about unknown tag {{include_example}} on two different computers (Linux and OSX). Looks like {{include_example}} is local in {{./docs/_plugins/include_example.rb}}, so maybe this is some kind of path issue where its not finding the local file ? > API Doc pages for Streaming with Kafka 0.10 not current > --- > > Key: SPARK-19767 > URL: https://issues.apache.org/jira/browse/SPARK-19767 > Project: Spark > Issue Type: Bug > Components: Structured Streaming >Affects Versions: 2.1.0 >Reporter: Nick Afshartous >Priority: Minor > > The API docs linked from the Spark Kafka 0.10 Integration page are not > current. For instance, on the page >https://spark.apache.org/docs/latest/streaming-kafka-0-10-integration.html > the code examples show the new API (i.e. class ConsumerStrategies). However, > following the links > API Docs --> (Scala | Java) > lead to API pages that do not have class ConsumerStrategies) . The API doc > package names also have {code}streaming.kafka{code} as opposed to > {code}streaming.kafka10{code} > as in the code examples on streaming-kafka-0-10-integration.html. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19767) API Doc pages for Streaming with Kafka 0.10 not current
[ https://issues.apache.org/jira/browse/SPARK-19767?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15897965#comment-15897965 ] Nick Afshartous commented on SPARK-19767: - I believe all the dependencies are installed and got this error about a missing tag {{'include_example'}} {code} SKIP_API=1 jekyll build Configuration file: none Source: /home/nafshartous/Projects/spark Destination: /home/nafshartous/Projects/spark/_site Incremental build: disabled. Enable with --incremental Generating... Build Warning: Layout 'global' requested in docs/api.md does not exist. Build Warning: Layout 'global' requested in docs/building-spark.md does not exist. Build Warning: Layout 'global' requested in docs/cluster-overview.md does not exist. Build Warning: Layout 'global' requested in docs/configuration.md does not exist. Build Warning: Layout 'global' requested in docs/contributing-to-spark.md does not exist. Build Warning: Layout 'global' requested in docs/ec2-scripts.md does not exist. Liquid Exception: Liquid syntax error (line 581): Unknown tag 'include_example' in docs/graphx-programming-guide.md jekyll 3.4.0 | Error: Liquid syntax error (line 581): Unknown tag 'include_example' {code} > API Doc pages for Streaming with Kafka 0.10 not current > --- > > Key: SPARK-19767 > URL: https://issues.apache.org/jira/browse/SPARK-19767 > Project: Spark > Issue Type: Bug > Components: Structured Streaming >Affects Versions: 2.1.0 >Reporter: Nick Afshartous >Priority: Minor > > The API docs linked from the Spark Kafka 0.10 Integration page are not > current. For instance, on the page >https://spark.apache.org/docs/latest/streaming-kafka-0-10-integration.html > the code examples show the new API (i.e. class ConsumerStrategies). However, > following the links > API Docs --> (Scala | Java) > lead to API pages that do not have class ConsumerStrategies) . The API doc > package names also have {code}streaming.kafka{code} as opposed to > {code}streaming.kafka10{code} > as in the code examples on streaming-kafka-0-10-integration.html. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Comment Edited] (SPARK-19767) API Doc pages for Streaming with Kafka 0.10 not current
[ https://issues.apache.org/jira/browse/SPARK-19767?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15888572#comment-15888572 ] Nick Afshartous edited comment on SPARK-19767 at 3/1/17 10:15 PM: -- Yes the code examples on the Integration Page are current. The issue with the linked API pages looks like more than incompleteness because the package name {code}org.apache.spark.streaming.kafka{code} should be {code}org.apache.spark.streaming.kafka10{code}. I'd be happy to help. Tried to build the doc running "jekyll build" from the docs dir and got the error below. Is this target broken or my env ? {code} [info] Note: Custom tags that could override future standard tags: @todo, @note, @tparam, @constructor, @groupname, @example, @group. To avoid potential overrides, use at least one period character (.) in custom tag names. [info] Note: Custom tags that were not seen: @todo, @tparam, @constructor, @groupname, @group [info] 1 error [info] 100 warnings [error] (spark/javaunidoc:doc) javadoc returned nonzero exit code [error] Total time: 198 s, completed Feb 28, 2017 11:56:20 AM jekyll 3.4.0 | Error: Unidoc generation failed {code} was (Author: nafshartous): Yes the code examples on the Integration Page are current. The issue with the linked API pages looks like more than incompleteness because the package names name {code}org.apache.spark.streaming.kafka{code} should be {code}org.apache.spark.streaming.kafka10{code}. I'd be happy to help. Tried to build the doc running "jekyll build" from the docs dir and got the error below. Is this target broken or my env ? {code} [info] Note: Custom tags that could override future standard tags: @todo, @note, @tparam, @constructor, @groupname, @example, @group. To avoid potential overrides, use at least one period character (.) in custom tag names. [info] Note: Custom tags that were not seen: @todo, @tparam, @constructor, @groupname, @group [info] 1 error [info] 100 warnings [error] (spark/javaunidoc:doc) javadoc returned nonzero exit code [error] Total time: 198 s, completed Feb 28, 2017 11:56:20 AM jekyll 3.4.0 | Error: Unidoc generation failed {code} > API Doc pages for Streaming with Kafka 0.10 not current > --- > > Key: SPARK-19767 > URL: https://issues.apache.org/jira/browse/SPARK-19767 > Project: Spark > Issue Type: Bug > Components: Structured Streaming >Affects Versions: 2.1.0 >Reporter: Nick Afshartous >Priority: Minor > > The API docs linked from the Spark Kafka 0.10 Integration page are not > current. For instance, on the page >https://spark.apache.org/docs/latest/streaming-kafka-0-10-integration.html > the code examples show the new API (i.e. class ConsumerStrategies). However, > following the links > API Docs --> (Scala | Java) > lead to API pages that do not have class ConsumerStrategies) . The API doc > package names also have {code}streaming.kafka{code} as opposed to > {code}streaming.kafka10{code} > as in the code examples on streaming-kafka-0-10-integration.html. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org