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Driver HA support using WriteAheadLog #14

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@tdas tdas commented Oct 4, 2014

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@tdas tdas closed this Nov 11, 2014
tdas pushed a commit that referenced this pull request Jan 21, 2015
Support ! boolean logic operator like NOT in sql as follows
select * from for_test where !(col1 > col2)

Author: YanTangZhai <hakeemzhai@tencent.com>
Author: Michael Armbrust <michael@databricks.com>

Closes apache#3555 from YanTangZhai/SPARK-4692 and squashes the following commits:

1a9f605 [YanTangZhai] Update HiveQuerySuite.scala
7c03c68 [YanTangZhai] Merge pull request #23 from apache/master
992046e [YanTangZhai] Update HiveQuerySuite.scala
ea618f4 [YanTangZhai] Update HiveQuerySuite.scala
192411d [YanTangZhai] Merge pull request #17 from YanTangZhai/master
e4c2c0a [YanTangZhai] Merge pull request #15 from apache/master
1e1ebb4 [YanTangZhai] Update HiveQuerySuite.scala
efc4210 [YanTangZhai] Update HiveQuerySuite.scala
bd2c444 [YanTangZhai] Update HiveQuerySuite.scala
1893956 [YanTangZhai] Merge pull request #14 from marmbrus/pr/3555
59e4de9 [Michael Armbrust] make hive test
718afeb [YanTangZhai] Merge pull request #12 from apache/master
950b21e [YanTangZhai] Update HiveQuerySuite.scala
74175b4 [YanTangZhai] Update HiveQuerySuite.scala
92242c7 [YanTangZhai] Update HiveQl.scala
6e643f8 [YanTangZhai] Merge pull request #11 from apache/master
e249846 [YanTangZhai] Merge pull request #10 from apache/master
d26d982 [YanTangZhai] Merge pull request #9 from apache/master
76d4027 [YanTangZhai] Merge pull request #8 from apache/master
03b62b0 [YanTangZhai] Merge pull request #7 from apache/master
8a00106 [YanTangZhai] Merge pull request #6 from apache/master
cbcba66 [YanTangZhai] Merge pull request #3 from apache/master
cdef539 [YanTangZhai] Merge pull request #1 from apache/master
tdas pushed a commit that referenced this pull request Apr 23, 2015
This PR try to speed up some python tests:

```
tests.py                       144s -> 103s      -41s
mllib/classification.py         24s -> 17s        -7s
mllib/regression.py             27s -> 15s       -12s
mllib/tree.py                   27s -> 13s       -14s
mllib/tests.py                  64s -> 31s       -33s
streaming/tests.py             185s -> 84s      -101s
```
Considering python3, the total saving will be 558s (almost 10 minutes) (core, and streaming run three times, mllib runs twice).

During testing, it will show used time for each test file:
```
Run core tests ...
Running test: pyspark/rdd.py ... ok (22s)
Running test: pyspark/context.py ... ok (16s)
Running test: pyspark/conf.py ... ok (4s)
Running test: pyspark/broadcast.py ... ok (4s)
Running test: pyspark/accumulators.py ... ok (4s)
Running test: pyspark/serializers.py ... ok (6s)
Running test: pyspark/profiler.py ... ok (5s)
Running test: pyspark/shuffle.py ... ok (1s)
Running test: pyspark/tests.py ... ok (103s)   144s
```

Author: Reynold Xin <rxin@databricks.com>
Author: Xiangrui Meng <meng@databricks.com>

Closes apache#5605 from rxin/python-tests-speed and squashes the following commits:

d08542d [Reynold Xin] Merge pull request #14 from mengxr/SPARK-6953
89321ee [Xiangrui Meng] fix seed in tests
3ad2387 [Reynold Xin] Merge pull request apache#5427 from davies/python_tests
tdas pushed a commit that referenced this pull request Jul 9, 2015
…into a single batch.

SQL
```
select * from tableA join tableB on (a > 3 and b = d) or (a > 3 and b = e)
```
Plan before modify
```
== Optimized Logical Plan ==
Project [a#293,b#294,c#295,d#296,e#297]
 Join Inner, Some(((a#293 > 3) && ((b#294 = d#296) || (b#294 = e#297))))
  MetastoreRelation default, tablea, None
  MetastoreRelation default, tableb, None
```
Plan after modify
```
== Optimized Logical Plan ==
Project [a#293,b#294,c#295,d#296,e#297]
 Join Inner, Some(((b#294 = d#296) || (b#294 = e#297)))
  Filter (a#293 > 3)
   MetastoreRelation default, tablea, None
  MetastoreRelation default, tableb, None
```

CombineLimits ==> Limit(If(LessThan(ne, le), ne, le), grandChild) and LessThan is in BooleanSimplification ,  so CombineLimits  must before BooleanSimplification and BooleanSimplification must before PushPredicateThroughJoin.

Author: Zhongshuai Pei <799203320@qq.com>
Author: DoingDone9 <799203320@qq.com>

Closes apache#6351 from DoingDone9/master and squashes the following commits:

20de7be [Zhongshuai Pei] Update Optimizer.scala
7bc7d28 [Zhongshuai Pei] Merge pull request #17 from apache/master
0ba5f42 [Zhongshuai Pei] Update Optimizer.scala
f8b9314 [Zhongshuai Pei] Update FilterPushdownSuite.scala
c529d9f [Zhongshuai Pei] Update FilterPushdownSuite.scala
ae3af6d [Zhongshuai Pei] Update FilterPushdownSuite.scala
a04ffae [Zhongshuai Pei] Update Optimizer.scala
11beb61 [Zhongshuai Pei] Update FilterPushdownSuite.scala
f2ee5fe [Zhongshuai Pei] Update Optimizer.scala
be6b1d5 [Zhongshuai Pei] Update Optimizer.scala
b01e622 [Zhongshuai Pei] Merge pull request #15 from apache/master
8df716a [Zhongshuai Pei] Update FilterPushdownSuite.scala
d98bc35 [Zhongshuai Pei] Update FilterPushdownSuite.scala
fa65718 [Zhongshuai Pei] Update Optimizer.scala
ab8e9a6 [Zhongshuai Pei] Merge pull request #14 from apache/master
14952e2 [Zhongshuai Pei] Merge pull request #13 from apache/master
f03fe7f [Zhongshuai Pei] Merge pull request #12 from apache/master
f12fa50 [Zhongshuai Pei] Merge pull request #10 from apache/master
f61210c [Zhongshuai Pei] Merge pull request #9 from apache/master
34b1a9a [Zhongshuai Pei] Merge pull request #8 from apache/master
802261c [DoingDone9] Merge pull request #7 from apache/master
d00303b [DoingDone9] Merge pull request #6 from apache/master
98b134f [DoingDone9] Merge pull request #5 from apache/master
161cae3 [DoingDone9] Merge pull request #4 from apache/master
c87e8b6 [DoingDone9] Merge pull request #3 from apache/master
cb1852d [DoingDone9] Merge pull request #2 from apache/master
c3f046f [DoingDone9] Merge pull request #1 from apache/master
tdas pushed a commit that referenced this pull request Apr 4, 2016
…gle batch

## What changes were proposed in this pull request?

This PR support multiple Python UDFs within single batch, also improve the performance.

```python
>>> from pyspark.sql.types import IntegerType
>>> sqlContext.registerFunction("double", lambda x: x * 2, IntegerType())
>>> sqlContext.registerFunction("add", lambda x, y: x + y, IntegerType())
>>> sqlContext.sql("SELECT double(add(1, 2)), add(double(2), 1)").explain(True)
== Parsed Logical Plan ==
'Project [unresolvedalias('double('add(1, 2)), None),unresolvedalias('add('double(2), 1), None)]
+- OneRowRelation$

== Analyzed Logical Plan ==
double(add(1, 2)): int, add(double(2), 1): int
Project [double(add(1, 2))#14,add(double(2), 1)#15]
+- Project [double(add(1, 2))#14,add(double(2), 1)#15]
   +- Project [pythonUDF0#16 AS double(add(1, 2))#14,pythonUDF0#18 AS add(double(2), 1)#15]
      +- EvaluatePython [add(pythonUDF1#17, 1)], [pythonUDF0#18]
         +- EvaluatePython [double(add(1, 2)),double(2)], [pythonUDF0#16,pythonUDF1#17]
            +- OneRowRelation$

== Optimized Logical Plan ==
Project [pythonUDF0#16 AS double(add(1, 2))#14,pythonUDF0#18 AS add(double(2), 1)#15]
+- EvaluatePython [add(pythonUDF1#17, 1)], [pythonUDF0#18]
   +- EvaluatePython [double(add(1, 2)),double(2)], [pythonUDF0#16,pythonUDF1#17]
      +- OneRowRelation$

== Physical Plan ==
WholeStageCodegen
:  +- Project [pythonUDF0#16 AS double(add(1, 2))#14,pythonUDF0#18 AS add(double(2), 1)#15]
:     +- INPUT
+- !BatchPythonEvaluation [add(pythonUDF1#17, 1)], [pythonUDF0#16,pythonUDF1#17,pythonUDF0#18]
   +- !BatchPythonEvaluation [double(add(1, 2)),double(2)], [pythonUDF0#16,pythonUDF1#17]
      +- Scan OneRowRelation[]
```

## How was this patch tested?

Added new tests.

Using the following script to benchmark 1, 2 and 3 udfs,
```
df = sqlContext.range(1, 1 << 23, 1, 4)
double = F.udf(lambda x: x * 2, LongType())
print df.select(double(df.id)).count()
print df.select(double(df.id), double(df.id + 1)).count()
print df.select(double(df.id), double(df.id + 1), double(df.id + 2)).count()
```
Here is the results:

N | Before | After  | speed up
---- |------------ | -------------|------
1 | 22 s | 7 s |  3.1X
2 | 38 s | 13 s | 2.9X
3 | 58 s | 16 s | 3.6X

This benchmark ran locally with 4 CPUs. For 3 UDFs, it launched 12 Python before before this patch, 4 process after this patch. After this patch, it will use less memory for multiple UDFs than before (less buffering).

Author: Davies Liu <davies@databricks.com>

Closes apache#12057 from davies/multi_udfs.
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