[ 
https://issues.apache.org/jira/browse/FLINK-5394?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

zhangjing updated FLINK-5394:
-----------------------------
    Description: 
The estimateRowCount method of DataSetCalc didn't work now. 
If I run the following code,
`
Table table = tableEnv
                                .fromDataSet(data, "a, b, c")
                                .groupBy("a")
                                .select("a, a.avg, b.sum, c.count")
                                .where("a == 1");
`
the cost of every node in Optimized node tree is :
`
DataSetAggregate(groupBy=[a], select=[a, AVG(a) AS TMP_0, SUM(b) AS TMP_1, 
COUNT(c) AS TMP_2]): rowcount = 1000.0, cumulative cost = {3000.0 rows, 5000.0 
cpu, 28000.0 io}
  DataSetCalc(select=[a, b, c], where=[=(a, 1)]): rowcount = 1000.0, cumulative 
cost = {2000.0 rows, 2000.0 cpu, 0.0 io}
      DataSetScan(table=[[_DataSetTable_0]]): rowcount = 1000.0, cumulative 
cost = {1000.0 rows, 1000.0 cpu, 0.0 io}
`
We expect the input rowcount of DataSetAggregate less than 1000, however the 
actual input rowcount is still 1000 because the the estimateRowCount method of 
DataSetCalc didn't work. 

There are two reasons caused to this:
1. when DataSetAggregate calls RelMetadataQuery.getRowCount(DataSetCalc) to 
estimate its input rowcount which would dispatch to RelMdRowCount.
2. DataSetCalc is subclass of SingleRel, so previous function call would match 
getRowCount(SingleRel rel, RelMetadataQuery mq) which would never use 
DataSetCalc.estimateRowCount.

I plan to resolve this problem by adding a FlinkRelMdRowCount which contains 
specific getRowCount of Flink RelNodes.

  was:
The estimateRowCount method of DataSetCalc didn't work now. 
If I run the following code,
`
Table table = tableEnv
                                .fromDataSet(data, "a, b, c")
                                .groupBy("a")
                                .select("a, a.avg, b.sum, c.count")
                                .where("a == 1");
`
the cost of every node in Optimized node tree is :
`
DataSetAggregate(groupBy=[a], select=[a, AVG(a) AS TMP_0, SUM(b) AS TMP_1, 
COUNT(c) AS TMP_2]): rowcount = 1000.0, cumulative cost = {3000.0 rows, 5000.0 
cpu, 28000.0 io}
|_  DataSetCalc(select=[a, b, c], where=[=(a, 1)]): rowcount = 1000.0, 
cumulative cost = {2000.0 rows, 2000.0 cpu, 0.0 io}
     |_ DataSetScan(table=[[_DataSetTable_0]]): rowcount = 1000.0, cumulative 
cost = {1000.0 rows, 1000.0 cpu, 0.0 io}
`
We expect the input rowcount of DataSetAggregate less than 1000, however the 
actual input rowcount is still 1000 because the the estimateRowCount method of 
DataSetCalc didn't work. 

There are two reasons caused to this:
1. when DataSetAggregate calls RelMetadataQuery.getRowCount(DataSetCalc) to 
estimate its input rowcount which would dispatch to RelMdRowCount.
2. DataSetCalc is subclass of SingleRel, so previous function call would match 
getRowCount(SingleRel rel, RelMetadataQuery mq) which would never use 
DataSetCalc.estimateRowCount.

I plan to resolve this problem by adding a FlinkRelMdRowCount which contains 
specific getRowCount of Flink RelNodes.


> the estimateRowCount method of DataSetCalc didn't work
> ------------------------------------------------------
>
>                 Key: FLINK-5394
>                 URL: https://issues.apache.org/jira/browse/FLINK-5394
>             Project: Flink
>          Issue Type: Bug
>          Components: Table API & SQL
>            Reporter: zhangjing
>            Assignee: zhangjing
>
> The estimateRowCount method of DataSetCalc didn't work now. 
> If I run the following code,
> `
> Table table = tableEnv
>                               .fromDataSet(data, "a, b, c")
>                               .groupBy("a")
>                               .select("a, a.avg, b.sum, c.count")
>                               .where("a == 1");
> `
> the cost of every node in Optimized node tree is :
> `
> DataSetAggregate(groupBy=[a], select=[a, AVG(a) AS TMP_0, SUM(b) AS TMP_1, 
> COUNT(c) AS TMP_2]): rowcount = 1000.0, cumulative cost = {3000.0 rows, 
> 5000.0 cpu, 28000.0 io}
>   DataSetCalc(select=[a, b, c], where=[=(a, 1)]): rowcount = 1000.0, 
> cumulative cost = {2000.0 rows, 2000.0 cpu, 0.0 io}
>       DataSetScan(table=[[_DataSetTable_0]]): rowcount = 1000.0, cumulative 
> cost = {1000.0 rows, 1000.0 cpu, 0.0 io}
> `
> We expect the input rowcount of DataSetAggregate less than 1000, however the 
> actual input rowcount is still 1000 because the the estimateRowCount method 
> of DataSetCalc didn't work. 
> There are two reasons caused to this:
> 1. when DataSetAggregate calls RelMetadataQuery.getRowCount(DataSetCalc) to 
> estimate its input rowcount which would dispatch to RelMdRowCount.
> 2. DataSetCalc is subclass of SingleRel, so previous function call would 
> match getRowCount(SingleRel rel, RelMetadataQuery mq) which would never use 
> DataSetCalc.estimateRowCount.
> I plan to resolve this problem by adding a FlinkRelMdRowCount which contains 
> specific getRowCount of Flink RelNodes.



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