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https://issues.apache.org/jira/browse/SPARK-24630?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16554043#comment-16554043
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Genmao Yu edited comment on SPARK-24630 at 7/24/18 10:07 AM:
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{{Structured Streaming supports standard SQL as the batch queries, so the users
can switch their queries between batch and streaming easily.}}
IIUC, there are some queries we can not switch from stream to batch, like
"*groupBy window a**ggregation"* or "*over window a**ggregation"* on stream.
Isn't it?
was (Author: unclegen):
{{Structured Streaming supports standard SQL as the batch queries, so the users
can switch their queries between batch and streaming easily.}}
IIUC, there are some queries we can not switch from stream to batch, like
"*groupBy window a**ggregation"*** or "*over window a**ggregation"*** on
stream. Isn't it?
> 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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