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My main concern is that, the new `FileCatalog` class hierarchy is really
complex now. Can we simplify it a little? or at least let's put a class
hierarchy chart(or text explanation) in PR descript
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Github user felixcheung commented on a diff in the pull request:
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--- Diff: R/pkg/R/column.R ---
@@ -70,11 +70,11 @@ setMethod("show", signature = "Column",
function(object) {
})
#' @rdname head
-set
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would it be possible to pull "6000" into a constant so it could be
found/changed in one shot?
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Github user rxin commented on the issue:
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@tejasapatil how does HIve store partitioning files?
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// The data whe
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Github user wangmiao1981 commented on the issue:
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I modified the code on `readString`. When len is negative, I read 3 bytes.
`NA` is read on scala side, which is correct field value. But the integer of
len is not serialized. It seems that R si
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@wangmiao1981 you are talking about Windows right?
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Hi, @rxin .
Could you review this again?
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--- Diff:
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LGTM, merging to master!
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Oh. Indeed. I thought it's a supported way since it works on Hive 1.2.
```sql
hive> load data local inpath '/data/t/*.txt' INTO TABLE x;
Loading data to table default.x
Table def
Github user priyankagargnitk commented on the issue:
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Hi rxin, Can we merge the same change in branch 1.6 as well... As we are
still using spark 1.6 and need this change?
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can you submit a pull request against that branch?
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No. Mac. I can always reproduce this issue on Mac. I modified code above on
scala side to make sure that `NA` is correctly serialized on scala side. But
the integer (i.e., length of `NA`) befor
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--- Diff:
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@@ -28,10 +28,11 @@ case class PythonUDF(
name: String,
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--- Diff: python/pyspark/sql/functions.py ---
@@ -1741,15 +1742,15 @@ def __call__(self, *cols):
@since(1.3)
-def udf(f, returnType=String
Github user gatorsmile commented on the issue:
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`ALTER TABLE`, `ANALYZE TABLE` and `CREATE TABLE LIKE` do not work well
when `spark.sql.debug` is set to true.
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Github user gatorsmile commented on the issue:
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Just FYI. https://github.com/apache/spark/pull/15478 shows at least three
DDL commands do not work properly when `spark.sql.debug` is set to `true`:
`ALTER TABLE`, `ANALYZE TABLE` and `CREATE TAB
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Jenkins, retest this please
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[SPARK-17254][SQL] Filter can stop when the condition is false if the child
output is sorted
## What changes were proposed in this pull request?
From
https://issues.apache.org/jira/secur
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Github user cloud-fan commented on the issue:
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I don't think it's a problem, we will only set this flag when debugging.
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Github user gatorsmile commented on the issue:
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Yeah, I see. This is just for showing the impact. Thanks!
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retest this please
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[SPARK-17884][SQL] To resolve Null pointer exception when casting from
empty string to interval type
## What changes were proposed in this pull request?
This change adds a check in ca
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Done. PR #15479
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Can one of the admins verify this patch?
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LGTM, merging to master!
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Github user MLnick commented on the issue:
https://github.com/apache/spark/pull/12761
@daniel-siegmann-aol ok - I think between @dbtsai and me we can run some
performance tests. I've been doing some work on Criteo Display Ad Challenge
data which makes a nice sparse benchmark dataset.
Github user MLnick commented on the issue:
https://github.com/apache/spark/pull/14653
jenkins test this please
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/14653
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/15360#discussion_r83365814
--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala ---
@@ -358,53 +358,189 @@ class StatisticsSuite extends QueryTest with
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/15360#discussion_r83366673
--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala ---
@@ -358,50 +358,180 @@ class StatisticsSuite extends QueryTest with
Github user wangmiao1981 commented on the issue:
https://github.com/apache/spark/pull/15421
I trace back to `createDataFrame.default`
...
jrdd <- getJRDD(lapply(rdd, function(x) x), "row")
srdd <- callJMethod(jrdd, "rdd")
sdf <- callJStatic("org.apache.spark.sql.a
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