[jira] [Updated] (SPARK-18339) Don't push down current_timestamp for filters in StructuredStreaming
[
https://issues.apache.org/jira/browse/SPARK-18339?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-18339:
-
Priority: Critical (was: Major)
> Don't push down current_timestamp for filters in StructuredStreaming
>
>
> Key: SPARK-18339
> URL: https://issues.apache.org/jira/browse/SPARK-18339
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
>Reporter: Burak Yavuz
>Assignee: Tyson Condie
>Priority: Critical
>
> For the following workflow:
> 1. I have a column called time which is at minute level precision in a
> Streaming DataFrame
> 2. I want to perform groupBy time, count
> 3. Then I want my MemorySink to only have the last 30 minutes of counts and I
> perform this by
> {code}
> .where('time >= current_timestamp().cast("long") - 30 * 60)
> {code}
> what happens is that the `filter` gets pushed down before the aggregation,
> and the filter happens on the source data for the aggregation instead of the
> result of the aggregation (where I actually want to filter).
> I guess the main issue here is that `current_timestamp` is non-deterministic
> in the streaming context and shouldn't be pushed down the filter.
> Does this require us to store the `current_timestamp` for each trigger of the
> streaming job, that is something to discuss.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-18339) Don't push down current_timestamp for filters in StructuredStreaming
[
https://issues.apache.org/jira/browse/SPARK-18339?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-18339:
-
Assignee: Tyson Condie
> Don't push down current_timestamp for filters in StructuredStreaming
>
>
> Key: SPARK-18339
> URL: https://issues.apache.org/jira/browse/SPARK-18339
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
>Reporter: Burak Yavuz
>Assignee: Tyson Condie
>
> For the following workflow:
> 1. I have a column called time which is at minute level precision in a
> Streaming DataFrame
> 2. I want to perform groupBy time, count
> 3. Then I want my MemorySink to only have the last 30 minutes of counts and I
> perform this by
> {code}
> .where('time >= current_timestamp().cast("long") - 30 * 60)
> {code}
> what happens is that the `filter` gets pushed down before the aggregation,
> and the filter happens on the source data for the aggregation instead of the
> result of the aggregation (where I actually want to filter).
> I guess the main issue here is that `current_timestamp` is non-deterministic
> in the streaming context and shouldn't be pushed down the filter.
> Does this require us to store the `current_timestamp` for each trigger of the
> streaming job, that is something to discuss.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-18339) Don't push down current_timestamp for filters in StructuredStreaming
[
https://issues.apache.org/jira/browse/SPARK-18339?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-18339:
-
Target Version/s: 2.1.0 (was: 2.2.0)
> Don't push down current_timestamp for filters in StructuredStreaming
>
>
> Key: SPARK-18339
> URL: https://issues.apache.org/jira/browse/SPARK-18339
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
>Reporter: Burak Yavuz
>
> For the following workflow:
> 1. I have a column called time which is at minute level precision in a
> Streaming DataFrame
> 2. I want to perform groupBy time, count
> 3. Then I want my MemorySink to only have the last 30 minutes of counts and I
> perform this by
> {code}
> .where('time >= current_timestamp().cast("long") - 30 * 60)
> {code}
> what happens is that the `filter` gets pushed down before the aggregation,
> and the filter happens on the source data for the aggregation instead of the
> result of the aggregation (where I actually want to filter).
> I guess the main issue here is that `current_timestamp` is non-deterministic
> in the streaming context and shouldn't be pushed down the filter.
> Does this require us to store the `current_timestamp` for each trigger of the
> streaming job, that is something to discuss.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-18339) Don't push down current_timestamp for filters in StructuredStreaming
[
https://issues.apache.org/jira/browse/SPARK-18339?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-18339:
-
Labels: (was: correctness)
> Don't push down current_timestamp for filters in StructuredStreaming
>
>
> Key: SPARK-18339
> URL: https://issues.apache.org/jira/browse/SPARK-18339
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
>Reporter: Burak Yavuz
>
> For the following workflow:
> 1. I have a column called time which is at minute level precision in a
> Streaming DataFrame
> 2. I want to perform groupBy time, count
> 3. Then I want my MemorySink to only have the last 30 minutes of counts and I
> perform this by
> {code}
> .where('time >= current_timestamp().cast("long") - 30 * 60)
> {code}
> what happens is that the `filter` gets pushed down before the aggregation,
> and the filter happens on the source data for the aggregation instead of the
> result of the aggregation (where I actually want to filter).
> I guess the main issue here is that `current_timestamp` is non-deterministic
> in the streaming context and shouldn't be pushed down the filter.
> Does this require us to store the `current_timestamp` for each trigger of the
> streaming job, that is something to discuss.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-18339) Don't push down current_timestamp for filters in StructuredStreaming
[
https://issues.apache.org/jira/browse/SPARK-18339?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-18339:
-
Target Version/s: 2.2.0
> Don't push down current_timestamp for filters in StructuredStreaming
>
>
> Key: SPARK-18339
> URL: https://issues.apache.org/jira/browse/SPARK-18339
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
>Reporter: Burak Yavuz
> Labels: correctness
>
> For the following workflow:
> 1. I have a column called time which is at minute level precision in a
> Streaming DataFrame
> 2. I want to perform groupBy time, count
> 3. Then I want my MemorySink to only have the last 30 minutes of counts and I
> perform this by
> {code}
> .where('time >= current_timestamp().cast("long") - 30 * 60)
> {code}
> what happens is that the `filter` gets pushed down before the aggregation,
> and the filter happens on the source data for the aggregation instead of the
> result of the aggregation (where I actually want to filter).
> I guess the main issue here is that `current_timestamp` is non-deterministic
> in the streaming context and shouldn't be pushed down the filter.
> Does this require us to store the `current_timestamp` for each trigger of the
> streaming job, that is something to discuss.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
