Github user dongjoon-hyun commented on the issue:
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When we turn on the option `true`, `t1` is broadcasted.
```
hive> set hive.auto.convert.join=true;
hive> EXPLAIN SELECT /*+ MAPJOIN(t1) */ * FROM (select * from t1) x, t2;
Warnin
Github user dongjoon-hyun commented on the issue:
https://github.com/apache/spark/pull/14132
Since `set hive.auto.convert.join=true;` is default, I think mapjoin hint
seems to work.
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Github user dongjoon-hyun commented on the issue:
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For the first case, I intentionally turn off the option to see the effect
of the hint only.
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Github user cloud-fan commented on the issue:
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For current hive, the `MAP_JOIN` hint is ignored totally right? How about
old hive(or other databases that support MAP_JOIN or BROADCAST_JOIN hint)? I
just wanna check the common rule to apply rel
GitHub user viirya opened a pull request:
https://github.com/apache/spark/pull/14388
[SPARK-16362][SQL] Support ArrayType and StructType in vectorized Parquet
reader
## What changes were proposed in this pull request?
Vectorization parquet reader now doesn't support complex
Github user viirya commented on the issue:
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Closed this PR in favor of the refactored one: #14388.
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Github user dongjoon-hyun commented on the issue:
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For `Table-Level Optimizer Hints` of MySQL, it applied to all table with
the same name.
> The hint applies to all tables that it names
http://dev.mysql.com/doc/refman/5.7/en/optimizer-h
Github user viirya commented on the issue:
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cc @cloud-fan @yhuai @liancheng @rxin Please review this change. Thanks.
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Github user petermaxlee commented on the issue:
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This should resolve the following two pull requests as well:
https://github.com/apache/spark/pull/14353
https://github.com/apache/spark/pull/14374
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GitHub user petermaxlee opened a pull request:
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[SPARK-16714][SQL] map, struct function should accept decimals with
different precision/scale
## What changes were proposed in this pull request?
This patch changes the type coercion rule f
Github user petermaxlee commented on the issue:
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@dongjoon-hyun I created a patch here:
https://github.com/apache/spark/pull/14389
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@biglobster @dongjoon-hyun I created a patch here:
https://github.com/apache/spark/pull/14389
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Could you add my testcase here, too?
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Also, please add `array` into the title and description.
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Github user petermaxlee commented on the issue:
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I was looking at the code, and I think this is a more general problem with
decimal widening. The same problem exists for least, and other functions.
```
scala> sql("select least(0.1,
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Github user petermaxlee commented on the issue:
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@dongjoon-hyun You only had one test case didn't you? I don't think that
test case is useful since it was testing specifically checkInputDataTypes,
which was not the right thing to test. Type co
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/14365#discussion_r72577696
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/SchemaMapping.scala ---
@@ -0,0 +1,80 @@
+/*
+ * Licensed to the Apache Software F
Github user petermaxlee commented on a diff in the pull request:
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--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/SQLTypeCoercionSuite.scala ---
@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Fo
Github user HyukjinKwon commented on the issue:
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Yea, for least and greatest, I opened this here
https://github.com/apache/spark/pull/14294. Actually, I am worried if allowing
lose of precision and fractions is okay.
I first thought
Github user dongjoon-hyun commented on the issue:
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@petermaxlee . Yep. I deleted my request, but you had better have a test
case with real columns on table data. :)
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cc @cloud-fan and @liancheng
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GitHub user maver1ck opened a pull request:
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[SPARK-15541] Casting ConcurrentHashMap to ConcurrentMap
## What changes were proposed in this pull request?
Casting ConcurrentHashMap to ConcurrentMap allows to run code compiled with
Ja
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Github user cloud-fan commented on the issue:
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cc @rxin @hvanhovell what do you think of this case?
`SELECT /*+ MAPJOIN(t1) */ * FROM (SELECT * FROM t1) x JOIN t1`
Applying the hint to the `t1` after JOIN looks more intuitive to me.
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/14296#discussion_r72579088
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -1207,6 +1207,17 @@ class Analyzer(
v
Github user dongjoon-hyun commented on the issue:
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Thank you for giving opinion.
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--- Diff:
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@@ -440,7 +440,7 @@ object TypeCoercion {
Github user dongjoon-hyun commented on the issue:
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For old hives, I can get the binary after Hive 1.0.
http://www-us.apache.org/dist/hive/
The above result was Hive 2.0 and 1.2. I think Hive 1.0 and 1.1 will be the
same as expected
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For @cloud-fan 's choice, I think I can block the subqueries which are
aliased by users.
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Github user cloud-fan commented on the issue:
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One problem of decimal type in Spark SQL is, the wider type of 2 decimal
types may be illegal(exceed system limitation), then we have to truncate and
suffer precision lose. This forces us to make
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Github user dongjoon-hyun commented on the issue:
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Hmm, maybe more sophisticate method is needed for both the following cases.
* SELECT /*+ MAPJOIN(t1) */ * FROM (SELECT * FROM t1) x JOIN t1
* SELECT /*+ MAPJOIN(t1) */ * FROM (SELEC
Github user cloud-fan commented on the issue:
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If we want to just fix these bugs, I think we should come up with a list
about which functions(need arguments of same type) can accept precision lose
and which can not.
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Github user hvanhovell commented on the issue:
https://github.com/apache/spark/pull/14132
I agree with @cloud-fan. It is confusing that the hint defined in the
top-level query gets applied to a subquery.
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Github user HyukjinKwon commented on the issue:
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FYI, I had a look before. Its map, array, greatest and least.
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Github user dongjoon-hyun commented on the issue:
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Thank you, @hvanhovell .
Then should we block all subquery or allow the following cases?
* SELECT /*+ MAPJOIN(t1) */ * FROM (SELECT * FROM t1) x JOIN t2;
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Github user dongjoon-hyun commented on the issue:
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At the implementation side, blocking all subqueries are easiest.
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Hi, @hvanhovell .
Could you review this PR again when you have some time?
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GitHub user viirya opened a pull request:
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[SPARK-16767][SQL] Add existsRecursively to UserDefinedType
## What changes were proposed in this pull request?
`DataType` has a method `existsRecursively` used to check recursively if a
da
Github user viirya commented on the issue:
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ping @cloud-fan Not sure if this is correct direction. Please let me know.
Thanks.
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Github user cloud-fan commented on the issue:
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`SELECT /*+ MAPJOIN(t1) */ * FROM (SELECT * FROM t1) x JOIN t2;`
yea I think this one should be noop
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Thank you for guidance, @cloud-fan !
I'll implement like that.
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Github user asfgit closed the pull request at:
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thanks, merging to master!
cc @yhuai @liancheng we will address your comments in follow up PRs if you
have any.
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Github user maver1ck commented on the issue:
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@jkbradley
Could you look at it ?
I think this is problem from:
https://issues.apache.org/jira/browse/SPARK-10086
Maybe we should merge this PR to branch-1.6 before testing ?
https:
Github user maver1ck commented on the issue:
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@jkbradley
What about merging this to branch-1.6
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Github user dongjoon-hyun commented on the issue:
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Hi, the followings are updated.
- Hints are not propagated into subqueries.
- Add new testcases
- `SELECT /*+ MAPJOIN(t1) */ * FROM t1 JOIN t1 JOIN t1 JOIN t1` (First
`t1`)
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/14392
[SPARK-16446] [SparkR] [ML] Gaussian Mixture Model wrapper in SparkR
## What changes were proposed in this pull request?
Gaussian Mixture Model wrapper in SparkR, similarly to R's
```mvnorma
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