[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[ericl]

Github user ericl commented on the issue:

https://github.com/apache/spark/pull/16090
  
Filed
https://issues.apache.org/jira/browse/SPARK-18725
https://issues.apache.org/jira/browse/SPARK-18726


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[cloud-fan]

Github user cloud-fan commented on the issue:

https://github.com/apache/spark/pull/16090
  
LGTM, merging to master/2.1!
@ericl please create tickets for the other 2 issues


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[ericl]

Github user ericl commented on the issue:

https://github.com/apache/spark/pull/16090
  
Yeah I was wondering if we should also try to fix that. It seems maybe not
as bad since unpartitioned tables usually aren't that big.

We can create separate tickets for investigating that, and also the
duplicate file scan issue (that might not be a regression).

On Sun, Dec 4, 2016, 12:05 AM Wenchen Fan  wrote:

> After looking more at the code, now I agree with your approach. One
> question, seems we still scan the files when creating a unpartitioned
> external data source table?
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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[cloud-fan]

Github user cloud-fan commented on the issue:

https://github.com/apache/spark/pull/16090
  
After looking more at the code, now I agree with your approach. One 
question, seems we still scan the files when creating a unpartitioned external 
data source table?


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[ericl]

Github user ericl commented on the issue:

https://github.com/apache/spark/pull/16090
  
Not sure I follow - could you explain more on why that would resolve the 
issue?

Btw, I reverted this pr to b405635, which passes all tests.


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[cloud-fan]

Github user cloud-fan commented on the issue:

https://github.com/apache/spark/pull/16090
  
If we are going to hack it, how about this?
```
val dataSource = DataSource(...)
if (classOf[FileFormat].isAssignableFrom(dataSource.providingClass)) {
  dataSource.getOrInferFileFormatSchema()
} else {
  dataSoure.resolveRelation().schema -> new StructType
}
```
Then we don't need to create `FileIndex` and scan files.


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[ericl]

Github user ericl commented on the issue:

https://github.com/apache/spark/pull/16090
  
Seems like the caching broke a bunch of tests. I'll take a look at this
again tomorrow.

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[ericl]

Github user ericl commented on the issue:

https://github.com/apache/spark/pull/16090
  
cc @rxin please merge unless wenchen gets to it first


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[ericl]

Github user ericl commented on the issue:

https://github.com/apache/spark/pull/16090
  
Fixed by adding a private cache to `Datasource`, which is used to avoid the 
duplicate file reads with InMemoryIndex.


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[ericl]

Github user ericl commented on the issue:

https://github.com/apache/spark/pull/16090
  
Seems like we also create InMemoryFileIndex twice for non-catalog tables. 
Let me try to fix that too.


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[ericl]

Github user ericl commented on the issue:

https://github.com/apache/spark/pull/16090
  
I looked at avoiding the creation of a CatalogFileIndex, but the way table 
resolution works right now, the only way is to create some sort of dummy file 
index class that does not support scans. It's not clear to me that is any 
better than just creating a CatalogFileIndex, which seems better than 
incorrectly creating an InMemoryFileIndex.


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[cloud-fan]

Github user cloud-fan commented on the issue:

https://github.com/apache/spark/pull/16090
  
My main concern is that, in `CreateDataSourceTableCommand`, we call 
`DataSource.resolveRelation` to infer the schema and partition columns. At that 
time, the table is not created yet, so logically we should not pass a 
`CatalogTable` to `DataSource` and create `CatalogFileIndex` inside it, which 
looks like a hack.

It seems to me that it's more logical to tweak the `InMemoryFileIndex` to 
scan the files lazily, to avoid unnecessary file scan for cases like this one.


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[SparkQA]

Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/16090
  
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[`89b0a64`](https://github.com/apache/spark/commit/89b0a6459effcfd575173bb4be4ba961dc9501f0).
 * This patch **fails Spark unit tests**.
 * This patch merges cleanly.
 * This patch adds no public classes.


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[SparkQA]

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https://github.com/apache/spark/pull/16090
  
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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

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https://github.com/apache/spark/pull/16090
  
**[Test build #69437 has 
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 for PR 16090 at commit 
[`275f6b9`](https://github.com/apache/spark/commit/275f6b92d88bea9518e42f61e02b872c4eade8ba).
 * This patch **fails Spark unit tests**.
 * This patch merges cleanly.
 * This patch adds no public classes.


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[SparkQA]

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https://github.com/apache/spark/pull/16090
  
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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

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https://github.com/apache/spark/pull/16090
  
**[Test build #69435 has 
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 * This patch **fails Scala style tests**.
 * This patch merges cleanly.
 * This patch adds no public classes.


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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

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https://github.com/apache/spark/pull/16090
  
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[GitHub] spark issue #16090: [SPARK-18661] [SQL] Creating a partitioned datasource ta...

[ericl]

Github user ericl commented on the issue:

https://github.com/apache/spark/pull/16090
  
@rxin


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