docFreq, termFreq, broadcast update #4
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…save broadcast as private var
|
Thanks @jkbradley. LGTM and I'll merge it now. |
hhbyyh
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docFreq, termFreq, broadcast update
hhbyyh
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JIRA issue [here](https://issues.apache.org/jira/browse/SPARK-5893). One thing to make clear, the `buckets` parameter, which is an array of `Double`, performs as split points. Say, ```scala buckets = Array(-0.5, 0.0, 0.5) ``` splits the real number into 4 ranges, (-inf, -0.5], (-0.5, 0.0], (0.0, 0.5], (0.5, +inf), which is encoded as 0, 1, 2, 3. Author: Xusen Yin <yinxusen@gmail.com> Author: Joseph K. Bradley <joseph@databricks.com> Closes apache#5980 from yinxusen/SPARK-5893 and squashes the following commits: dc8c843 [Xusen Yin] Merge pull request #4 from jkbradley/yinxusen-SPARK-5893 1ca973a [Joseph K. Bradley] one more bucketizer test 34f124a [Joseph K. Bradley] Removed lowerInclusive, upperInclusive params from Bucketizer, and used splits instead. eacfcfa [Xusen Yin] change ML attribute from splits into buckets c3cc770 [Xusen Yin] add more unit test for binary search 3a16cc2 [Xusen Yin] refine comments and names ac77859 [Xusen Yin] fix style error fb30d79 [Xusen Yin] fix and test binary search 2466322 [Xusen Yin] refactor Bucketizer 11fb00a [Xusen Yin] change it into an Estimator 998bc87 [Xusen Yin] check buckets 4024cf1 [Xusen Yin] add test suite 5fe190e [Xusen Yin] add bucketizer (cherry picked from commit 35fb42a) Signed-off-by: Joseph K. Bradley <joseph@databricks.com>
hhbyyh
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…" into true or false directly SQL ``` select key from src where 3 in (4, 5); ``` Before ``` == Optimized Logical Plan == Project [key#12] Filter 3 INSET (5,4) MetastoreRelation default, src, None ``` After ``` == Optimized Logical Plan == LocalRelation [key#228], [] ``` Author: Zhongshuai Pei <799203320@qq.com> Author: DoingDone9 <799203320@qq.com> Closes apache#5972 from DoingDone9/InToFalse and squashes the following commits: 4c722a2 [Zhongshuai Pei] Update predicates.scala abe2bbb [Zhongshuai Pei] Update Optimizer.scala fa461a5 [Zhongshuai Pei] Update Optimizer.scala e34c28a [Zhongshuai Pei] Update predicates.scala 24739bd [Zhongshuai Pei] Update ConstantFoldingSuite.scala f4dbf50 [Zhongshuai Pei] Update ConstantFoldingSuite.scala 35ceb7a [Zhongshuai Pei] Update Optimizer.scala 36c194e [Zhongshuai Pei] Update Optimizer.scala 2e8f6ca [Zhongshuai Pei] Update Optimizer.scala 14952e2 [Zhongshuai Pei] Merge pull request apache#13 from apache/master f03fe7f [Zhongshuai Pei] Merge pull request apache#12 from apache/master f12fa50 [Zhongshuai Pei] Merge pull request apache#10 from apache/master f61210c [Zhongshuai Pei] Merge pull request apache#9 from apache/master 34b1a9a [Zhongshuai Pei] Merge pull request apache#8 from apache/master 802261c [DoingDone9] Merge pull request apache#7 from apache/master d00303b [DoingDone9] Merge pull request apache#6 from apache/master 98b134f [DoingDone9] Merge pull request apache#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 (cherry picked from commit 4b5e1fe) Signed-off-by: Michael Armbrust <michael@databricks.com>
hhbyyh
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…l operators This patch introduces `SparkPlanTest`, a base class for unit tests of SparkPlan physical operators. This is analogous to Spark SQL's existing `QueryTest`, which does something similar for end-to-end tests with actual queries. These helper methods provide nicer error output when tests fail and help developers to avoid writing lots of boilerplate in order to execute manually constructed physical plans. Author: Josh Rosen <joshrosen@databricks.com> Author: Josh Rosen <rosenville@gmail.com> Author: Michael Armbrust <michael@databricks.com> Closes apache#6885 from JoshRosen/spark-plan-test and squashes the following commits: f8ce275 [Josh Rosen] Fix some IntelliJ inspections and delete some dead code 84214be [Josh Rosen] Add an extra column which isn't part of the sort ae1896b [Josh Rosen] Provide implicits automatically a80f9b0 [Josh Rosen] Merge pull request #4 from marmbrus/pr/6885 d9ab1e4 [Michael Armbrust] Add simple resolver c60a44d [Josh Rosen] Manually bind references 996332a [Josh Rosen] Add types so that tests compile a46144a [Josh Rosen] WIP (cherry picked from commit 207a98c) Signed-off-by: Michael Armbrust <michael@databricks.com>
hhbyyh
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…l` in IF/CASEWHEN
## What changes were proposed in this pull request?
Currently, `SimplifyConditionals` handles `true` and `false` to optimize branches. This PR improves `SimplifyConditionals` to take advantage of `null` conditions for `if` and `CaseWhen` expressions, too.
**Before**
```
scala> sql("SELECT IF(null, 1, 0)").explain()
== Physical Plan ==
WholeStageCodegen
: +- Project [if (null) 1 else 0 AS (IF(CAST(NULL AS BOOLEAN), 1, 0))#4]
: +- INPUT
+- Scan OneRowRelation[]
scala> sql("select case when cast(null as boolean) then 1 else 2 end").explain()
== Physical Plan ==
WholeStageCodegen
: +- Project [CASE WHEN null THEN 1 ELSE 2 END AS CASE WHEN CAST(NULL AS BOOLEAN) THEN 1 ELSE 2 END#14]
: +- INPUT
+- Scan OneRowRelation[]
```
**After**
```
scala> sql("SELECT IF(null, 1, 0)").explain()
== Physical Plan ==
WholeStageCodegen
: +- Project [0 AS (IF(CAST(NULL AS BOOLEAN), 1, 0))#4]
: +- INPUT
+- Scan OneRowRelation[]
scala> sql("select case when cast(null as boolean) then 1 else 2 end").explain()
== Physical Plan ==
WholeStageCodegen
: +- Project [2 AS CASE WHEN CAST(NULL AS BOOLEAN) THEN 1 ELSE 2 END#4]
: +- INPUT
+- Scan OneRowRelation[]
```
**Hive**
```
hive> select if(null,1,2);
OK
2
hive> select case when cast(null as boolean) then 1 else 2 end;
OK
2
```
## How was this patch tested?
Pass the Jenkins tests (including new extended test cases).
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes apache#12122 from dongjoon-hyun/SPARK-14338.
hhbyyh
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Jul 24, 2017
…pressions
## What changes were proposed in this pull request?
This PR changes the direction of expression transformation in the DecimalPrecision rule. Previously, the expressions were transformed down, which led to incorrect result types when decimal expressions had other decimal expressions as their operands. The root cause of this issue was in visiting outer nodes before their children. Consider the example below:
```
val inputSchema = StructType(StructField("col", DecimalType(26, 6)) :: Nil)
val sc = spark.sparkContext
val rdd = sc.parallelize(1 to 2).map(_ => Row(BigDecimal(12)))
val df = spark.createDataFrame(rdd, inputSchema)
// Works correctly since no nested decimal expression is involved
// Expected result type: (26, 6) * (26, 6) = (38, 12)
df.select($"col" * $"col").explain(true)
df.select($"col" * $"col").printSchema()
// Gives a wrong result since there is a nested decimal expression that should be visited first
// Expected result type: ((26, 6) * (26, 6)) * (26, 6) = (38, 12) * (26, 6) = (38, 18)
df.select($"col" * $"col" * $"col").explain(true)
df.select($"col" * $"col" * $"col").printSchema()
```
The example above gives the following output:
```
// Correct result without sub-expressions
== Parsed Logical Plan ==
'Project [('col * 'col) AS (col * col)#4]
+- LogicalRDD [col#1]
== Analyzed Logical Plan ==
(col * col): decimal(38,12)
Project [CheckOverflow((promote_precision(cast(col#1 as decimal(26,6))) * promote_precision(cast(col#1 as decimal(26,6)))), DecimalType(38,12)) AS (col * col)#4]
+- LogicalRDD [col#1]
== Optimized Logical Plan ==
Project [CheckOverflow((col#1 * col#1), DecimalType(38,12)) AS (col * col)#4]
+- LogicalRDD [col#1]
== Physical Plan ==
*Project [CheckOverflow((col#1 * col#1), DecimalType(38,12)) AS (col * col)#4]
+- Scan ExistingRDD[col#1]
// Schema
root
|-- (col * col): decimal(38,12) (nullable = true)
// Incorrect result with sub-expressions
== Parsed Logical Plan ==
'Project [(('col * 'col) * 'col) AS ((col * col) * col)apache#11]
+- LogicalRDD [col#1]
== Analyzed Logical Plan ==
((col * col) * col): decimal(38,12)
Project [CheckOverflow((promote_precision(cast(CheckOverflow((promote_precision(cast(col#1 as decimal(26,6))) * promote_precision(cast(col#1 as decimal(26,6)))), DecimalType(38,12)) as decimal(26,6))) * promote_precision(cast(col#1 as decimal(26,6)))), DecimalType(38,12)) AS ((col * col) * col)apache#11]
+- LogicalRDD [col#1]
== Optimized Logical Plan ==
Project [CheckOverflow((cast(CheckOverflow((col#1 * col#1), DecimalType(38,12)) as decimal(26,6)) * col#1), DecimalType(38,12)) AS ((col * col) * col)apache#11]
+- LogicalRDD [col#1]
== Physical Plan ==
*Project [CheckOverflow((cast(CheckOverflow((col#1 * col#1), DecimalType(38,12)) as decimal(26,6)) * col#1), DecimalType(38,12)) AS ((col * col) * col)apache#11]
+- Scan ExistingRDD[col#1]
// Schema
root
|-- ((col * col) * col): decimal(38,12) (nullable = true)
```
## How was this patch tested?
This PR was tested with available unit tests. Moreover, there are tests to cover previously failing scenarios.
Author: aokolnychyi <anton.okolnychyi@sap.com>
Closes apache#18583 from aokolnychyi/spark-21332.
hhbyyh
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Oct 22, 2019
…pressions
## What changes were proposed in this pull request?
This PR changes the direction of expression transformation in the DecimalPrecision rule. Previously, the expressions were transformed down, which led to incorrect result types when decimal expressions had other decimal expressions as their operands. The root cause of this issue was in visiting outer nodes before their children. Consider the example below:
```
val inputSchema = StructType(StructField("col", DecimalType(26, 6)) :: Nil)
val sc = spark.sparkContext
val rdd = sc.parallelize(1 to 2).map(_ => Row(BigDecimal(12)))
val df = spark.createDataFrame(rdd, inputSchema)
// Works correctly since no nested decimal expression is involved
// Expected result type: (26, 6) * (26, 6) = (38, 12)
df.select($"col" * $"col").explain(true)
df.select($"col" * $"col").printSchema()
// Gives a wrong result since there is a nested decimal expression that should be visited first
// Expected result type: ((26, 6) * (26, 6)) * (26, 6) = (38, 12) * (26, 6) = (38, 18)
df.select($"col" * $"col" * $"col").explain(true)
df.select($"col" * $"col" * $"col").printSchema()
```
The example above gives the following output:
```
// Correct result without sub-expressions
== Parsed Logical Plan ==
'Project [('col * 'col) AS (col * col)#4]
+- LogicalRDD [col#1]
== Analyzed Logical Plan ==
(col * col): decimal(38,12)
Project [CheckOverflow((promote_precision(cast(col#1 as decimal(26,6))) * promote_precision(cast(col#1 as decimal(26,6)))), DecimalType(38,12)) AS (col * col)#4]
+- LogicalRDD [col#1]
== Optimized Logical Plan ==
Project [CheckOverflow((col#1 * col#1), DecimalType(38,12)) AS (col * col)#4]
+- LogicalRDD [col#1]
== Physical Plan ==
*Project [CheckOverflow((col#1 * col#1), DecimalType(38,12)) AS (col * col)#4]
+- Scan ExistingRDD[col#1]
// Schema
root
|-- (col * col): decimal(38,12) (nullable = true)
// Incorrect result with sub-expressions
== Parsed Logical Plan ==
'Project [(('col * 'col) * 'col) AS ((col * col) * col)apache#11]
+- LogicalRDD [col#1]
== Analyzed Logical Plan ==
((col * col) * col): decimal(38,12)
Project [CheckOverflow((promote_precision(cast(CheckOverflow((promote_precision(cast(col#1 as decimal(26,6))) * promote_precision(cast(col#1 as decimal(26,6)))), DecimalType(38,12)) as decimal(26,6))) * promote_precision(cast(col#1 as decimal(26,6)))), DecimalType(38,12)) AS ((col * col) * col)apache#11]
+- LogicalRDD [col#1]
== Optimized Logical Plan ==
Project [CheckOverflow((cast(CheckOverflow((col#1 * col#1), DecimalType(38,12)) as decimal(26,6)) * col#1), DecimalType(38,12)) AS ((col * col) * col)apache#11]
+- LogicalRDD [col#1]
== Physical Plan ==
*Project [CheckOverflow((cast(CheckOverflow((col#1 * col#1), DecimalType(38,12)) as decimal(26,6)) * col#1), DecimalType(38,12)) AS ((col * col) * col)apache#11]
+- Scan ExistingRDD[col#1]
// Schema
root
|-- ((col * col) * col): decimal(38,12) (nullable = true)
```
## How was this patch tested?
This PR was tested with available unit tests. Moreover, there are tests to cover previously failing scenarios.
Author: aokolnychyi <anton.okolnychyi@sap.com>
Closes apache#18583 from aokolnychyi/spark-21332.
(cherry picked from commit 0be5fb4)
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
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renamed docFreq to DF, termFreq to TF, and added fractional support. save broadcast as private var
CC: @hhbyyh @mengxr