[jira] [Updated] (SPARK-24630) SPIP: Support SQLStreaming in Spark

2018-06-22 Thread Jackey Lee (JIRA)


 [ 
https://issues.apache.org/jira/browse/SPARK-24630?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Jackey Lee updated SPARK-24630:
---
Summary: SPIP: Support SQLStreaming in Spark  (was: Support SQLStreaming in 
Spark)

> SPIP: Support SQLStreaming in Spark
> ---
>
> Key: SPARK-24630
> URL: https://issues.apache.org/jira/browse/SPARK-24630
> Project: Spark
>  Issue Type: Improvement
>  Components: SQL
>Affects Versions: 2.2.0, 2.2.1
>Reporter: Jackey Lee
>Priority: Minor
>  Labels: SQLStreaming
>
> At present, KafkaSQL, Flink SQL(which is actually based on Calcite), 
> SQLStream, StormSQL all provide a stream type SQL interface, with which users 
> with little knowledge about streaming,  can easily develop a flow system 
> processing model. In Spark, we can also support SQL API based on 
> StructStreamig.
> To support for SQL Streaming, there are two key points: 
> 1, Analysis should be able to parse streaming type SQL. 
> 2, Analyzer should be able to map metadata information to the corresponding 
> Relation. 



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[jira] [Updated] (SPARK-24630) SPIP: Support SQLStreaming in Spark

2018-06-22 Thread Jackey Lee (JIRA)


 [ 
https://issues.apache.org/jira/browse/SPARK-24630?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Jackey Lee updated SPARK-24630:
---
Attachment: SQLStreaming SPIP.pdf

> SPIP: Support SQLStreaming in Spark
> ---
>
> Key: SPARK-24630
> URL: https://issues.apache.org/jira/browse/SPARK-24630
> Project: Spark
>  Issue Type: Improvement
>  Components: SQL
>Affects Versions: 2.2.0, 2.2.1
>Reporter: Jackey Lee
>Priority: Minor
>  Labels: SQLStreaming
> Attachments: SQLStreaming SPIP.pdf
>
>
> At present, KafkaSQL, Flink SQL(which is actually based on Calcite), 
> SQLStream, StormSQL all provide a stream type SQL interface, with which users 
> with little knowledge about streaming,  can easily develop a flow system 
> processing model. In Spark, we can also support SQL API based on 
> StructStreamig.
> To support for SQL Streaming, there are two key points: 
> 1, Analysis should be able to parse streaming type SQL. 
> 2, Analyzer should be able to map metadata information to the corresponding 
> Relation. 



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[jira] [Updated] (SPARK-24630) SPIP: Support SQLStreaming in Spark

2018-06-27 Thread Shixiong Zhu (JIRA)


 [ 
https://issues.apache.org/jira/browse/SPARK-24630?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Shixiong Zhu updated SPARK-24630:
-
Component/s: (was: SQL)
 Structured Streaming

> SPIP: Support SQLStreaming in Spark
> ---
>
> Key: SPARK-24630
> URL: https://issues.apache.org/jira/browse/SPARK-24630
> Project: Spark
>  Issue Type: Improvement
>  Components: Structured Streaming
>Affects Versions: 2.2.0, 2.2.1
>Reporter: Jackey Lee
>Priority: Minor
>  Labels: SQLStreaming
> Attachments: SQLStreaming SPIP.pdf
>
>
> At present, KafkaSQL, Flink SQL(which is actually based on Calcite), 
> SQLStream, StormSQL all provide a stream type SQL interface, with which users 
> with little knowledge about streaming,  can easily develop a flow system 
> processing model. In Spark, we can also support SQL API based on 
> StructStreamig.
> To support for SQL Streaming, there are two key points: 
> 1, Analysis should be able to parse streaming type SQL. 
> 2, Analyzer should be able to map metadata information to the corresponding 
> Relation. 



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[jira] [Updated] (SPARK-24630) SPIP: Support SQLStreaming in Spark

2018-07-30 Thread Genmao Yu (JIRA)


 [ 
https://issues.apache.org/jira/browse/SPARK-24630?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Genmao Yu updated SPARK-24630:
--
Attachment: image-2018-07-30-18-06-30-506.png

> SPIP: Support SQLStreaming in Spark
> ---
>
> Key: SPARK-24630
> URL: https://issues.apache.org/jira/browse/SPARK-24630
> Project: Spark
>  Issue Type: Improvement
>  Components: Structured Streaming
>Affects Versions: 2.2.0, 2.2.1
>Reporter: Jackey Lee
>Priority: Minor
>  Labels: SQLStreaming
> Attachments: SQLStreaming SPIP.pdf, image-2018-07-30-18-06-30-506.png
>
>
> At present, KafkaSQL, Flink SQL(which is actually based on Calcite), 
> SQLStream, StormSQL all provide a stream type SQL interface, with which users 
> with little knowledge about streaming,  can easily develop a flow system 
> processing model. In Spark, we can also support SQL API based on 
> StructStreamig.
> To support for SQL Streaming, there are two key points: 
> 1, Analysis should be able to parse streaming type SQL. 
> 2, Analyzer should be able to map metadata information to the corresponding 
> Relation. 



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[jira] [Updated] (SPARK-24630) SPIP: Support SQLStreaming in Spark

2018-07-30 Thread Genmao Yu (JIRA)


 [ 
https://issues.apache.org/jira/browse/SPARK-24630?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Genmao Yu updated SPARK-24630:
--
Attachment: image-2018-07-30-18-48-38-352.png

> SPIP: Support SQLStreaming in Spark
> ---
>
> Key: SPARK-24630
> URL: https://issues.apache.org/jira/browse/SPARK-24630
> Project: Spark
>  Issue Type: Improvement
>  Components: Structured Streaming
>Affects Versions: 2.2.0, 2.2.1
>Reporter: Jackey Lee
>Priority: Minor
>  Labels: SQLStreaming
> Attachments: SQLStreaming SPIP.pdf, 
> image-2018-07-30-18-06-30-506.png, image-2018-07-30-18-48-38-352.png
>
>
> At present, KafkaSQL, Flink SQL(which is actually based on Calcite), 
> SQLStream, StormSQL all provide a stream type SQL interface, with which users 
> with little knowledge about streaming,  can easily develop a flow system 
> processing model. In Spark, we can also support SQL API based on 
> StructStreamig.
> To support for SQL Streaming, there are two key points: 
> 1, Analysis should be able to parse streaming type SQL. 
> 2, Analyzer should be able to map metadata information to the corresponding 
> Relation. 



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[jira] [Updated] (SPARK-24630) SPIP: Support SQLStreaming in Spark

2018-07-30 Thread Genmao Yu (JIRA)


 [ 
https://issues.apache.org/jira/browse/SPARK-24630?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Genmao Yu updated SPARK-24630:
--
Attachment: (was: image-2018-07-30-18-06-30-506.png)

> SPIP: Support SQLStreaming in Spark
> ---
>
> Key: SPARK-24630
> URL: https://issues.apache.org/jira/browse/SPARK-24630
> Project: Spark
>  Issue Type: Improvement
>  Components: Structured Streaming
>Affects Versions: 2.2.0, 2.2.1
>Reporter: Jackey Lee
>Priority: Minor
>  Labels: SQLStreaming
> Attachments: SQLStreaming SPIP.pdf
>
>
> At present, KafkaSQL, Flink SQL(which is actually based on Calcite), 
> SQLStream, StormSQL all provide a stream type SQL interface, with which users 
> with little knowledge about streaming,  can easily develop a flow system 
> processing model. In Spark, we can also support SQL API based on 
> StructStreamig.
> To support for SQL Streaming, there are two key points: 
> 1, Analysis should be able to parse streaming type SQL. 
> 2, Analyzer should be able to map metadata information to the corresponding 
> Relation. 



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[jira] [Updated] (SPARK-24630) SPIP: Support SQLStreaming in Spark

2018-07-30 Thread Genmao Yu (JIRA)


 [ 
https://issues.apache.org/jira/browse/SPARK-24630?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Genmao Yu updated SPARK-24630:
--
Attachment: (was: image-2018-07-30-18-48-38-352.png)

> SPIP: Support SQLStreaming in Spark
> ---
>
> Key: SPARK-24630
> URL: https://issues.apache.org/jira/browse/SPARK-24630
> Project: Spark
>  Issue Type: Improvement
>  Components: Structured Streaming
>Affects Versions: 2.2.0, 2.2.1
>Reporter: Jackey Lee
>Priority: Minor
>  Labels: SQLStreaming
> Attachments: SQLStreaming SPIP.pdf
>
>
> At present, KafkaSQL, Flink SQL(which is actually based on Calcite), 
> SQLStream, StormSQL all provide a stream type SQL interface, with which users 
> with little knowledge about streaming,  can easily develop a flow system 
> processing model. In Spark, we can also support SQL API based on 
> StructStreamig.
> To support for SQL Streaming, there are two key points: 
> 1, Analysis should be able to parse streaming type SQL. 
> 2, Analyzer should be able to map metadata information to the corresponding 
> Relation. 



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[jira] [Updated] (SPARK-24630) SPIP: Support SQLStreaming in Spark

2018-12-25 Thread Jackey Lee (JIRA)


 [ 
https://issues.apache.org/jira/browse/SPARK-24630?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Jackey Lee updated SPARK-24630:
---
Attachment: (was: SQLStreaming SPIP.pdf)

> SPIP: Support SQLStreaming in Spark
> ---
>
> Key: SPARK-24630
> URL: https://issues.apache.org/jira/browse/SPARK-24630
> Project: Spark
>  Issue Type: Improvement
>  Components: Structured Streaming
>Affects Versions: 2.2.0, 2.2.1
>Reporter: Jackey Lee
>Priority: Minor
>  Labels: SQLStreaming
>
> At present, KafkaSQL, Flink SQL(which is actually based on Calcite), 
> SQLStream, StormSQL all provide a stream type SQL interface, with which users 
> with little knowledge about streaming,  can easily develop a flow system 
> processing model. In Spark, we can also support SQL API based on 
> StructStreamig.
> To support for SQL Streaming, there are two key points: 
> 1, Analysis should be able to parse streaming type SQL. 
> 2, Analyzer should be able to map metadata information to the corresponding 
> Relation. 



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[jira] [Updated] (SPARK-24630) SPIP: Support SQLStreaming in Spark

2018-12-25 Thread Jackey Lee (JIRA)


 [ 
https://issues.apache.org/jira/browse/SPARK-24630?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Jackey Lee updated SPARK-24630:
---
Attachment: SQLStreaming SPIP V2.pdf

> SPIP: Support SQLStreaming in Spark
> ---
>
> Key: SPARK-24630
> URL: https://issues.apache.org/jira/browse/SPARK-24630
> Project: Spark
>  Issue Type: Improvement
>  Components: Structured Streaming
>Affects Versions: 2.2.0, 2.2.1
>Reporter: Jackey Lee
>Priority: Minor
>  Labels: SQLStreaming
> Attachments: SQLStreaming SPIP V2.pdf
>
>
> At present, KafkaSQL, Flink SQL(which is actually based on Calcite), 
> SQLStream, StormSQL all provide a stream type SQL interface, with which users 
> with little knowledge about streaming,  can easily develop a flow system 
> processing model. In Spark, we can also support SQL API based on 
> StructStreamig.
> To support for SQL Streaming, there are two key points: 
> 1, Analysis should be able to parse streaming type SQL. 
> 2, Analyzer should be able to map metadata information to the corresponding 
> Relation. 



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