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GitHub user manishatGit opened a pull request:
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[SPARK-16765] [Example] Added example for k-means to predict with
categorical features
## What changes were proposed in this pull request?
Added example for K-Means as Pipeline API
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Github user cloud-fan commented on the issue:
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Oh sorry I misread our parser rules. `varchar(length)` is supported but the
`length` is ignored. I checked with hive again, looks like the only unsupported
data type is `UNIONTYPE`
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Github user gatorsmile commented on the issue:
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```SCALA
TestHive.sessionState.metadataHive.runSqlHive("CREATE TABLE test (id
varchar(50))")
TestHive.sessionState.metadataHive.runSqlHive("INSERT INTO TABLE test
VALUES ('4')")
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Github user cloud-fan commented on a diff in the pull request:
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--- Diff: examples/src/main/r/RSparkSQLExample.R ---
@@ -18,31 +18,43 @@
library(SparkR)
# $example on:init_session$
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Github user yhuai commented on the issue:
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@liancheng after second thought, I think it makes sense to also merge it to
branch 2.0 to avoid potential conflicts on doc fixes.
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Github user cloud-fan commented on the issue:
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for a hive table(created by hive) with `varchar(length)` column, we can
describe it but can't read data from it before this PR. Now we can't describe
it. Do you think we should fix it? BTW there
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Thanks. But, what are specific cases are not supported? If there is any
case, we should make change to support that, right?
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--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/HashBenchmark.scala ---
@@ -119,11 +146,12 @@ object HashBenchmark {
.add("map",
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> Do we know which hive type strings cannot be parsed by spark?
`varchar(length)` and `char(length)`. see
https://github.com/apache/spark/pull/14363#discussion_r72735867 for what we
Github user dongjoon-hyun commented on a diff in the pull request:
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--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
---
@@ -280,6 +267,32 @@ trait CheckAnalysis extends
Github user dongjoon-hyun commented on the issue:
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Thank you for review, @hvanhovell .
For the recursive CTE queries, traditional DBMS supports optional
`RECURSIVE` keyword which computing **closures**, i.e., it iterates the
subquery
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@srowen will this pr be meged into branch-2.0?
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Github user holdenk commented on the issue:
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This looks good to me pending since annotation bump in Python. Personally I
think a docs update could be a good follow up - but since were tagging it as an
expert param for now I think this makes
Github user holdenk commented on a diff in the pull request:
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--- Diff: python/pyspark/ml/recommendation.py ---
@@ -332,6 +338,20 @@ def getFinalStorageLevel(self):
"""
return
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Kafka failure seems unlikely to be related, jenkins retest this please.
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Github user NarineK commented on a diff in the pull request:
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--- Diff: docs/sparkr.md ---
@@ -429,19 +431,19 @@ result <- gapplyCollect(
df,
"waiting",
function(key, x) {
-y <-
Github user NarineK commented on a diff in the pull request:
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--- Diff: docs/sparkr.md ---
@@ -398,23 +398,25 @@ and Spark.
{% highlight r %}
# Determine six waiting times with the largest eruption time
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Github user kiszk commented on a diff in the pull request:
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--- Diff:
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---
@@ -1441,6 +1441,12 @@ object PushPredicateThroughJoin
Github user holdenk commented on a diff in the pull request:
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--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetCompatibilityTest.scala
---
@@ -119,8 +119,18 @@ private[sql]
Github user asfgit closed the pull request at:
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Github user asfgit closed the pull request at:
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Github user yhuai commented on the issue:
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LGTM. Merging to master and branch 2.0.
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Github user HyukjinKwon commented on the issue:
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I might have to make a follow-up for..
- making `DatatypeConverter.parseDateTime` to be safe with early dates
- enabling `TimestampType` tests in `JsonHadoopFsRelationSuite`
Github user sundapeng commented on the issue:
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Thank @BryanCutler and @srowen for your review
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Github user gatorsmile commented on the issue:
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@rxin That is definitely true! I had the same concern when changing the
code.
Now, we are having two types of tables: one is Data source tables and the
other is Hive tables. The default
Github user yhuai commented on the issue:
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LGTM. Thanks. Merging to master.
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Github user HyukjinKwon commented on the issue:
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I think it is okay. Just to make sure,
- **This writes date and timestamps fine**:
```scala
val path = "/tmp"
val date = java.sql.Date.valueOf("1970-01-01")
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[SPARK-16258][SparkR][WIP] Gapply add key attach option
## What changes were proposed in this pull request?
The following pull request addresses the new feature request described in
Github user rxin commented on the issue:
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cc @yhuai
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Github user rxin commented on the issue:
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We already have default sources. It is very confusing to have default
format on top of that.
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Github user HyukjinKwon commented on a diff in the pull request:
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--- Diff:
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---
@@ -119,8 +119,18 @@
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--- Diff:
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---
@@ -119,8 +119,18 @@
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Github user holdenk commented on the issue:
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Now that the 2.0 release is fully out (release artifacts and all) - maybe
@rxin would have a chance to take another look at this (and @techaddict who did
some AccumulatorV2 work as well)?
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Github user holdenk commented on the issue:
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@HyukjinKwon no worries - just wanted to make sure we weren't accidentally
duplicating eachothers efforts :)
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Github user holdenk commented on the issue:
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Just for good measure lets re-run the jenkins tests.
Jenkins retest this please.
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Github user hvanhovell commented on a diff in the pull request:
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--- Diff:
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---
@@ -280,6 +267,32 @@ trait CheckAnalysis extends
Github user hvanhovell commented on a diff in the pull request:
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--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -131,17 +131,17 @@ class Analyzer(
def
Github user hvanhovell commented on the issue:
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@dongjoon-hyun I think this has merit. I do have one question, what do
other databases do? Like postgresql, mysql, sqlserver and others?
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Ok, this looks pretty good. One overall comment: We are basically
blacklisting operators here (which is fine IMO), should we check if there any
other operators we should about? If there are we
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Github user lovexi commented on the issue:
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Oh, my bad. Added unit test in `MetricsSystemSuite ` for this already.
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Github user yhuai commented on the issue:
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Do we know which hive type strings cannot be parsed by spark?
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Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/14430#discussion_r72910955
--- Diff:
sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveWindowFunctionQuerySuite.scala
---
@@ -89,15 +89,6 @@ class
GitHub user gatorsmile opened a pull request:
https://github.com/apache/spark/pull/14430
[SPARK-16825] [SQL] Replace hive.default.fileformat by
spark.sql.default.fileformat
### What changes were proposed in this pull request?
Currently, we are using `hive.default.fileformat`,
Github user yhuai commented on a diff in the pull request:
https://github.com/apache/spark/pull/14363#discussion_r72910844
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/interface.scala
---
@@ -78,28 +78,6 @@ object CatalogStorageFormat {
}
Github user deanchen commented on the issue:
https://github.com/apache/spark/pull/14279
@srowen ltgm, thanks for chiming in!
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