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Github user ouyangxiaochen commented on the issue:
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I am sorry that I did't grasp the key points of your question. In Hive, if
there are data files under the specified path while creating an external table,
then Hive will identify the files
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Github user cloud-fan commented on a diff in the pull request:
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--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/sources/PartitionedWriteSuite.scala
---
@@ -92,6 +111,16 @@ class PartitionedWriteSuite extends
Github user windpiger commented on a diff in the pull request:
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--- Diff:
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---
@@ -92,6 +96,47 @@ class PartitionedWriteSuite extends
Github user windpiger commented on a diff in the pull request:
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--- Diff:
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Github user zsxwing commented on the issue:
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Made one pass. Looks good overall. Just some nits.
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Github user wangmiao1981 commented on a diff in the pull request:
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--- Diff: R/pkg/R/mllib_clustering.R ---
@@ -225,10 +225,12 @@ setMethod("spark.kmeans", signature(data =
"SparkDataFrame", formula = "formula"
Github user admackin commented on the issue:
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I've addressed all the problems I think â code style now fixed,
MLTestingUtils patched (and verified all MLLib test cases still pass), and
added a test case for zero-valued labels
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Github user gatorsmile commented on the issue:
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Please keep updating your PR description. For example, this PR is not
relying on `manual tests`. In addition, you also need to summarize what this PR
did. List more details to help reviewers
Github user gatorsmile commented on the issue:
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Let me rephrase it. If the directory specified in the `LOCATION` spec
contains the other files, what does Hive behave?
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Github user gatorsmile commented on the issue:
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First, please change the PR title to `[SPARK-19115] [SQL] Supporting Create
External Table Like Location`
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Github user gatorsmile commented on the issue:
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The connectors by some DBMS vendors are using the UNLOAD utility, which
performs much better, and build the RDD in the connectors.
Normally, JDBC is not a good option for large table
Github user srowen commented on the issue:
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Metrics evaluate the clustering though; the details of the algorithm are
irrelevant. This still clusters points in a continuous space so you can measure
WSSSE.
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Github user gatorsmile commented on the issue:
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:- ) No perfect solution, but we should use the [metric
prefix](https://en.wikipedia.org/wiki/Metric_prefix) when the number is huge.
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Github user gatorsmile commented on the issue:
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SQLServer has three ways to show the plan: graphical plans, text plans, and
XML plans. Actually, it is pretty advanced. When using the text plans, users
can set the output formats:
1.
Github user actuaryzhang commented on the issue:
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@yanboliang Thanks. Seems to have passed tests.
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Github user cloud-fan commented on the issue:
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thanks, merging to master!
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Github user dongjoon-hyun commented on the issue:
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The only failure is irrelevant to this PR.
```
[info] - set spark.sql.warehouse.dir *** FAILED *** (5 minutes, 0 seconds)
[info] Timeout of './bin/spark-submit' '--class'
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/16668#discussion_r97254989
--- Diff: R/pkg/R/DataFrame.R ---
@@ -3406,3 +3406,28 @@ setMethod("randomSplit",
}
sapply(sdfs, dataFrame)
Github user dongjoon-hyun commented on the issue:
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Retest this please.
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Github user gatorsmile commented on the issue:
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As of MySQL 5.7.3, the EXPLAIN statement is changed so that the effect of
the EXTENDED keyword is always enabled.
```
mysql> EXPLAIN EXTENDED
-> SELECT t1.a, t1.a IN (SELECT t2.a
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Github user gatorsmile commented on the issue:
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PostgreSQL has [a few different options in the EXPLAIN
command](https://www.postgresql.org/docs/9.3/static/sql-explain.html):
```
EXPLAIN SELECT * FROM foo WHERE i = 4;
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/16552#discussion_r97253775
--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala
---
@@ -1353,6 +1353,15 @@ class HiveDDLSuite
Github user gatorsmile commented on the issue:
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DB2 has a tool to format the contents of the EXPLAIN tables. Below is an
example of the output with explanation:
**
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Github user windpiger commented on the issue:
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In hive:
1. read a table with non-existing path, no exception and return 0 rows
2. read a table with non-permission path, throw runtime exception
```
FAILED: SemanticException
Github user gatorsmile commented on the issue:
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LGTM pending test.
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Thanks! Merging to master.
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LGTM pending test
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thanks, merging to master!
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Github user gatorsmile commented on the issue:
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Let us do some research how the other RDBMSs are doing it? For example,
Oracle
```
SQL> explain plan for select * from product;
Explained.
SQL> select * from
Github user wzhfy commented on the issue:
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@rxin Can we add a flag to enable or disable it? Currently there's no other
way to see size and row count except debugging.
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Github user djvulee commented on the issue:
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@HyukjinKwon One assumption behind this design is that the specified column
has index in most real scenario, so the table scan cost is not much high.
What I observed is that most large
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LGTM
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LGTM
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Github user rxin commented on the issue:
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sorry this explain plan makes no sense -- it is impossible to read.
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Github user dongjoon-hyun commented on a diff in the pull request:
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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@@ -982,6 +982,33 @@ class SQLQuerySuite extends QueryTest with
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/16636
Ideally the table schema must be specified or inferred before saving to
metastore, however, for hive serde tables, we have to save it to metastore
first, and let the hive metastore to infer the
Github user dongjoon-hyun commented on a diff in the pull request:
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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@@ -982,6 +982,33 @@ class SQLQuerySuite extends QueryTest with
Github user dongjoon-hyun commented on a diff in the pull request:
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
---
@@ -982,6 +982,33 @@ class SQLQuerySuite extends QueryTest with
Github user viirya commented on a diff in the pull request:
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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@@ -982,6 +982,33 @@ class SQLQuerySuite extends QueryTest with
Github user dongjoon-hyun commented on a diff in the pull request:
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
---
@@ -982,6 +982,33 @@ class SQLQuerySuite extends QueryTest with
Github user viirya commented on a diff in the pull request:
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
---
@@ -982,6 +982,33 @@ class SQLQuerySuite extends QueryTest with
Github user actuaryzhang commented on the issue:
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@yanboliang Thanks so much for your detailed review. Your suggestions make
lots of sense and I have included all of them in the new commit. Let me know if
there is any other change needed.
Github user HyukjinKwon commented on the issue:
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FWIW, I am negative of this approach too. It does not look a good solution
to require full table scans to resolve skew between partitions.
As said, it is not good for a large table.
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
---
@@ -982,6 +982,33 @@ class SQLQuerySuite extends QueryTest with
Github user viirya commented on a diff in the pull request:
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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@@ -982,6 +982,33 @@ class SQLQuerySuite extends QueryTest with
Github user dongjoon-hyun commented on a diff in the pull request:
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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Looks good, I'll merge if it passes test. Thanks.
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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Github user wzhfy commented on the issue:
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@hvanhovell I've updated the description which shows a simple example.
The explained plan will become hard to read when joining many tables and
sizeInBytes is computed by the simple way
Github user dongjoon-hyun commented on the issue:
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Thank you, @viirya .
I noticed that `spark.sessionState.conf.clear()` is useless. I removed that.
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Github user actuaryzhang commented on the issue:
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@yanboliang Thanks for the quick response. How about the new commit, where
I just change the value from `getFamily` to lower case when necessary, i.e., in
the calculation of p-value and
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
---
@@ -982,6 +982,33 @@ class SQLQuerySuite extends QueryTest with
Github user yanboliang commented on the issue:
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@actuaryzhang I think the change is not appropriate, the function
```getFamily``` should return the raw value that users specified, this is the
cause that I didn't change them in #16516 .
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Github user actuaryzhang commented on the issue:
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I would prefer that `getFamily` returns lower case values directly, because
using `getFamily.toLowerCase` can get very cumbersome and I use this a lot in
another PR #16344. If we want to keep
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/16636#discussion_r97247351
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/command/DDLSuite.scala
---
@@ -1527,6 +1527,21 @@ class DDLSuite extends QueryTest with
Github user koertkuipers commented on the issue:
https://github.com/apache/spark/pull/16479
i will just copy the conversion code over for now thx
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GitHub user actuaryzhang opened a pull request:
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[SPARK-19155][ML] make getFamily case insensitive
## What changes were proposed in this pull request?
This is a supplement to PR #16516 which did not make the value from
`getFamily` case
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Test PASSed.
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/16579
Merged build finished. Test PASSed.
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