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[GitHub] [arrow-datafusion] Ted-Jiang opened a new pull request, #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Ted-Jiang opened a new pull request, #2192:
URL: https://github.com/apache/arrow-datafusion/pull/2192
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[GitHub] [arrow-datafusion] yjshen merged pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Posted by GitBox <gi...@apache.org>.
yjshen merged PR #2192:
URL: https://github.com/apache/arrow-datafusion/pull/2192
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[GitHub] [arrow-datafusion] liukun4515 commented on pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Posted by GitBox <gi...@apache.org>.
liukun4515 commented on PR #2192:
URL: https://github.com/apache/arrow-datafusion/pull/2192#issuecomment-1096498971
I think we should add the function in https://github.com/apache/arrow-datafusion/blob/28a6da3d2d175eb9d2f4ff8a6ea58e7c22dae97c/ballista/rust/core/proto/datafusion.proto#L203 proto
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[GitHub] [arrow-datafusion] Ted-Jiang commented on pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Posted by GitBox <gi...@apache.org>.
Ted-Jiang commented on PR #2192:
URL: https://github.com/apache/arrow-datafusion/pull/2192#issuecomment-1097510156
> I think we should add the function in
>
> https://github.com/apache/arrow-datafusion/blob/28a6da3d2d175eb9d2f4ff8a6ea58e7c22dae97c/ballista/rust/core/proto/datafusion.proto#L203
>
> proto
Yes , but there is some issue in #2221
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[GitHub] [arrow-datafusion] yjshen commented on a diff in pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Posted by GitBox <gi...@apache.org>.
yjshen commented on code in PR #2192:
URL: https://github.com/apache/arrow-datafusion/pull/2192#discussion_r846936268
##########
ballista/rust/client/src/context.rs:
##########
@@ -718,6 +719,199 @@ mod tests {
)
.await
.unwrap();
+
+ let df = context.sql("select min(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------+",
+ "| MIN(test.id) |",
+ "+--------------+",
+ "| 0 |",
+ "+--------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context.sql("select max(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------+",
+ "| MAX(test.id) |",
+ "+--------------+",
+ "| 7 |",
+ "+--------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context.sql("select SUM(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------+",
+ "| SUM(test.id) |",
+ "+--------------+",
+ "| 28 |",
+ "+--------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context.sql("select AVG(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------+",
+ "| AVG(test.id) |",
+ "+--------------+",
+ "| 3.5 |",
+ "+--------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context.sql("select COUNT(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+----------------+",
+ "| COUNT(test.id) |",
+ "+----------------+",
+ "| 8 |",
+ "+----------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select approx_distinct(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+-------------------------+",
+ "| APPROXDISTINCT(test.id) |",
+ "+-------------------------+",
+ "| 8 |",
+ "+-------------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select ARRAY_AGG(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------------------+",
+ "| ARRAYAGG(test.id) |",
+ "+--------------------------+",
+ "| [4, 5, 6, 7, 2, 3, 0, 1] |",
+ "+--------------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context.sql("select VAR(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+-------------------+",
+ "| VARIANCE(test.id) |",
+ "+-------------------+",
+ "| 6.000000000000001 |",
+ "+-------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select VAR_POP(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+----------------------+",
+ "| VARIANCEPOP(test.id) |",
+ "+----------------------+",
+ "| 5.250000000000001 |",
+ "+----------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select VAR_SAMP(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+-------------------+",
+ "| VARIANCE(test.id) |",
+ "+-------------------+",
+ "| 6.000000000000001 |",
+ "+-------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select STDDEV(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------------+",
+ "| STDDEV(test.id) |",
+ "+--------------------+",
+ "| 2.4494897427831783 |",
+ "+--------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select STDDEV_SAMP(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------------+",
+ "| STDDEV(test.id) |",
+ "+--------------------+",
+ "| 2.4494897427831783 |",
+ "+--------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select COVAR(id, tinyint_col) from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------------------------------+",
+ "| COVARIANCE(test.id,test.tinyint_col) |",
+ "+--------------------------------------+",
+ "| 0.28571428571428586 |",
+ "+--------------------------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select CORR(id, tinyint_col) from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+---------------------------------------+",
+ "| CORRELATION(test.id,test.tinyint_col) |",
+ "+---------------------------------------+",
+ "| 0.21821789023599245 |",
+ "+---------------------------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select approx_percentile_cont_with_weight(\"id\", 2, 0.5) from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+---------------------------------------------------------------+",
+ "| APPROXPERCENTILECONTWITHWEIGHT(test.id,Int64(2),Float64(0.5)) |",
Review Comment:
🤔 hard to read a little bit.
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[GitHub] [arrow-datafusion] Ted-Jiang commented on pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Posted by GitBox <gi...@apache.org>.
Ted-Jiang commented on PR #2192:
URL: https://github.com/apache/arrow-datafusion/pull/2192#issuecomment-1094495108
@houqp @yjshen plz take a look.
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[GitHub] [arrow-datafusion] Ted-Jiang commented on a diff in pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Posted by GitBox <gi...@apache.org>.
Ted-Jiang commented on code in PR #2192:
URL: https://github.com/apache/arrow-datafusion/pull/2192#discussion_r849028186
##########
ballista/rust/client/src/context.rs:
##########
@@ -718,6 +719,199 @@ mod tests {
)
.await
.unwrap();
+
+ let df = context.sql("select min(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------+",
+ "| MIN(test.id) |",
+ "+--------------+",
+ "| 0 |",
+ "+--------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context.sql("select max(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------+",
+ "| MAX(test.id) |",
+ "+--------------+",
+ "| 7 |",
+ "+--------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context.sql("select SUM(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------+",
+ "| SUM(test.id) |",
+ "+--------------+",
+ "| 28 |",
+ "+--------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context.sql("select AVG(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------+",
+ "| AVG(test.id) |",
+ "+--------------+",
+ "| 3.5 |",
+ "+--------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context.sql("select COUNT(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+----------------+",
+ "| COUNT(test.id) |",
+ "+----------------+",
+ "| 8 |",
+ "+----------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select approx_distinct(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+-------------------------+",
+ "| APPROXDISTINCT(test.id) |",
+ "+-------------------------+",
+ "| 8 |",
+ "+-------------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select ARRAY_AGG(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------------------+",
+ "| ARRAYAGG(test.id) |",
+ "+--------------------------+",
+ "| [4, 5, 6, 7, 2, 3, 0, 1] |",
+ "+--------------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context.sql("select VAR(\"id\") from test").await.unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+-------------------+",
+ "| VARIANCE(test.id) |",
+ "+-------------------+",
+ "| 6.000000000000001 |",
+ "+-------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select VAR_POP(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+----------------------+",
+ "| VARIANCEPOP(test.id) |",
+ "+----------------------+",
+ "| 5.250000000000001 |",
+ "+----------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select VAR_SAMP(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+-------------------+",
+ "| VARIANCE(test.id) |",
+ "+-------------------+",
+ "| 6.000000000000001 |",
+ "+-------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select STDDEV(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------------+",
+ "| STDDEV(test.id) |",
+ "+--------------------+",
+ "| 2.4494897427831783 |",
+ "+--------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select STDDEV_SAMP(\"id\") from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------------+",
+ "| STDDEV(test.id) |",
+ "+--------------------+",
+ "| 2.4494897427831783 |",
+ "+--------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select COVAR(id, tinyint_col) from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+--------------------------------------+",
+ "| COVARIANCE(test.id,test.tinyint_col) |",
+ "+--------------------------------------+",
+ "| 0.28571428571428586 |",
+ "+--------------------------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select CORR(id, tinyint_col) from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+---------------------------------------+",
+ "| CORRELATION(test.id,test.tinyint_col) |",
+ "+---------------------------------------+",
+ "| 0.21821789023599245 |",
+ "+---------------------------------------+",
+ ];
+ assert_result_eq(expected, &*res);
+
+ let df = context
+ .sql("select approx_percentile_cont_with_weight(\"id\", 2, 0.5) from test")
+ .await
+ .unwrap();
+ let res = df.collect().await.unwrap();
+ let expected = vec![
+ "+---------------------------------------------------------------+",
+ "| APPROXPERCENTILECONTWITHWEIGHT(test.id,Int64(2),Float64(0.5)) |",
Review Comment:
I thinks this name is align with proto file, it try to rewrite `debug` or `display` of this struct , it not works😂
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[GitHub] [arrow-datafusion] Ted-Jiang commented on pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Posted by GitBox <gi...@apache.org>.
Ted-Jiang commented on PR #2192:
URL: https://github.com/apache/arrow-datafusion/pull/2192#issuecomment-1097509398
>
There is some issue in #2221
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[GitHub] [arrow-datafusion] Ted-Jiang commented on pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Posted by GitBox <gi...@apache.org>.
Ted-Jiang commented on PR #2192:
URL: https://github.com/apache/arrow-datafusion/pull/2192#issuecomment-1097508664
> I think we should add the function in
>
> https://github.com/apache/arrow-datafusion/blob/28a6da3d2d175eb9d2f4ff8a6ea58e7c22dae97c/ballista/rust/core/proto/datafusion.proto#L203
>
> proto
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[GitHub] [arrow-datafusion] Ted-Jiang closed pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Posted by GitBox <gi...@apache.org>.
Ted-Jiang closed pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
URL: https://github.com/apache/arrow-datafusion/pull/2192
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[GitHub] [arrow-datafusion] Ted-Jiang commented on pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Posted by GitBox <gi...@apache.org>.
Ted-Jiang commented on PR #2192:
URL: https://github.com/apache/arrow-datafusion/pull/2192#issuecomment-1097509602
>
There is some issue in https://github.com/apache/arrow-datafusion/issues/2221
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[GitHub] [arrow-datafusion] liukun4515 commented on pull request #2192: [Ballista] Enable ApproxPercentileWithWeight in Ballista and fill UT
Posted by GitBox <gi...@apache.org>.
liukun4515 commented on PR #2192:
URL: https://github.com/apache/arrow-datafusion/pull/2192#issuecomment-1098076947
> > I think we should add the function in
> > https://github.com/apache/arrow-datafusion/blob/28a6da3d2d175eb9d2f4ff8a6ea58e7c22dae97c/ballista/rust/core/proto/datafusion.proto#L203
> >
> > proto
>
> Yes , but there is some issue in #2221 but in df it just rewrite `APPROX_MEDIAN` to `APPROX_PERCENTILE(0.5)`
My thought is that we should add
```
APPROX_PERCENTILE_CONT_WITH_WEIGHT = 16;
```
behind the `APPROX_MEDIAN=15; ` in the proto file.
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