If you compile with -fomit-frame-pointer, which is the default on recent
versions of gcc, the stack unwinding code in FOnStack will not work. This
is just a non-critical debugging aid, so let's just remove it altogether.

Signed-off-by: NBhuvnesh Chaudhary <bchaudhary@pivotal.io>

This commit creates a new file `CCastUtils.cpp` which maintains all the
cast functions.

The following functions are moved from `CUtils.cpp` to `CCastUtils.cpp`:
```
* BOOL FBinaryCoercibleCastedScId(CExpression *pexpr, CColRef *pcr)
* BOOL FBinaryCoercibleCastedScId(CExpression *pexpr)
* const CColRef *PcrExtractFromScIdOrCastScId(CExpression *pexpr)
* CExpression *PexprCast( IMemoryPool *pmp, CMDAccessor *pmda, const
CColRef *pcr, IMDId *pmdidDest)
* BOOL FBinaryCoercibleCast(CExpression *pexpr)
* CExpression *PexprWithoutBinaryCoercibleCasts(CExpression *pexpr)
```

The following functions are moved from `CPredicateUtils.cpp` to
`CCastUtils.cpp`:

```
* DrgPexpr *PdrgpexprCastEquality(IMemoryPool *pmp, CExpression *pexpr)
* CExpression *PexprAddCast(IMemoryPool *pmp, CExpression *pexprPred)
* CExpression *PexprCast(IMemoryPool *pmp, CMDAccessor *pmda,
CExpression *pexpr, IMDId *pmdidDest)
```
Signed-off-by: NDhanashree Kashid <dkashid@pivotal.io>
Signed-off-by: NBhuvnesh Chaudhary <bchaudhary@pivotal.io>

Currently executor crashes for following query with ORCA ON :
```
CREATE TABLE FOO(a
integer NOT NULL, b double precision[]); SELECT b FROM foo UNION ALL SELECT
ARRAY[90, 90] as Cont_features;
```

In this query, we are appending an integer array (ARRAY[90, 90]) to a double
precision array (foo.b) and hence we need to apply a cast on ARRAY[90, 90] to
generate ARRAY[90, 90]::double precision[].
In gpdb5 there is not direct function available that can cast array of any type
to array of any other type. So in relcache to dxl translator we look into the
array elements and get their type and try to find a cast function for them.
For this query, source type is 23 (integer) and dest type is 701 (double precision)
 and we try to find if we have a conversion function for 23 -> 701.
Since that is available we send that function to ORCA as follows:
```
<dxl:MDCast
Mdid="3.1007.1.0;1022.1.0" Name="float8" BinaryCoercible="false"
SourceTypeId="0.1007.1.0" DestinationTypeId="0.1022.1.0"
CastFuncId="0.316.1.0"/>
```
Here we are misinforming ORCA by specifying that function with id 316 is available
to convert type 1007 (integer array) to 1022 (double precision) array.
However Function id 316 is simple int4 to float8 conversion function and it CAN NOT
convert an array of int4 to array of double precision.
ORCA generates a plan using this function but executor crashes while executing this
function because this function can not handle arrays.

This commit adds a new ArrayCoerceCast MetaData object which will be constructed
when we need to convert an array of one type to another; instead of constructing
Cast Metadata.

`CMDArrayCoerceCastGPDB` extends `CMDCastGPDB` in that it includes necessary information
to generate `CScalarArrayCoerceExpr`.

In Relcache Translator on GPDB, we will construct an object of `CMDArrayCoerceCastGPDB`
instead of `CMDCastGPDB` depending on the coercion path determined by `FCastFunc`.

Added relevant test cases.

Ref [#149524459]
Signed-off-by: NEkta Khanna <ekhanna@pivotal.io>

Add NULL check before calling IMDId FValid()

Most of time is spent on running the 4 minidumps in CalibratedCostModel test.
The 4 minidumps are already tested in other test suites. Moreover, it just
executes the minidump, doesn't even compare the generaeted plan.

CalibratedCostModel is default in GPDB right now, and most minidumps use
calibrated cost model, that will also test CalibratedCostModel at the same
time. So remove EresUnittest_CalibratedCostModel. Cut down the debug runtime
of CCostTest from 814829 ms to 458 ms.

Signed-off-by: NJemish Patel <jpatel@pivotal.io>

projections from the inner side.

For the query: `explain select * from foo where foo.a in (select foo.b from bar);`
ORCA generates 2 diff plans based on the size of `bar`.  If bar is a small table,
then  ORCA picks the plan below as it is cheaper to broadcast bar.

```
Physical plan #1:
+--CPhysicalMotionGather(master)   rows:1   width:76  rebinds:1   cost:1324032.133055   origin: [Grp:4, GrpExpr:19]
   +--CPhysicalCorrelatedInLeftSemiNLJoin("b" (1))   rows:1   width:76  rebinds:1   cost:1324032.133025   origin: [Grp:4, GrpExpr:18]
      |--CPhysicalFilter   rows:1   width:38  rebinds:1   cost:431.000092   origin: [Grp:9, GrpExpr:1]
      |  |--CPhysicalTableScan "foo" ("foo")   rows:1   width:38  rebinds:1   cost:431.000021   origin: [Grp:0, GrpExpr:1]
      |  +--CScalarCmp (=)   origin: [Grp:6, GrpExpr:0]
      |     |--CScalarIdent "a" (0)   origin: [Grp:2, GrpExpr:0]
      |     +--CScalarIdent "b" (1)   origin: [Grp:5, GrpExpr:0]
      |--CPhysicalSpool   rows:1   width:38  rebinds:1   cost:431.000026   origin: [Grp:1, GrpExpr:3]
      |  +--CPhysicalMotionBroadcast    rows:1   width:38  rebinds:1   cost:431.000025   origin: [Grp:1, GrpExpr:2]
      |     +--CPhysicalTableScan "bar" ("bar")   rows:1   width:38  rebinds:1   cost:431.000007   origin: [Grp:1, GrpExpr:1]
      +--CScalarConst (1)   origin: [Grp:8, GrpExpr:0]
```
However if bar is a large table, ORCA will decorrelate it into a inner join
and produces a plan as below:

```
Physical plan #2:
+--CPhysicalMotionGather(master)   rows:1   width:76  rebinds:1   cost:1324095.808700   origin: [Grp:4, GrpExpr:19]
   +--CPhysicalInnerNLJoin   rows:1   width:76  rebinds:1   cost:1324095.808670   origin: [Grp:4, GrpExpr:14]
      |--CPhysicalFilter   rows:1   width:38  rebinds:1   cost:431.000092   origin: [Grp:9, GrpExpr:1]
      |  |--CPhysicalTableScan "foo" ("foo")   rows:1   width:38  rebinds:1   cost:431.000021   origin: [Grp:0, GrpExpr:1]
      |  +--CScalarCmp (=)   origin: [Grp:6, GrpExpr:0]
      |     |--CScalarIdent "a" (0)   origin: [Grp:2, GrpExpr:0]
      |     +--CScalarIdent "b" (1)   origin: [Grp:5, GrpExpr:0]
      |--CPhysicalSpool   rows:1   width:38  rebinds:1   cost:431.062210   origin: [Grp:32, GrpExpr:5]
      |  +--CPhysicalMotionBroadcast    rows:1   width:38  rebinds:1   cost:431.062209   origin: [Grp:32, GrpExpr:6]
      |     +--CPhysicalLimit <empty> global   rows:1   width:38  rebinds:1   cost:431.062155   origin: [Grp:32, GrpExpr:2]
      |        |--CPhysicalMotionGather(master)   rows:1   width:38  rebinds:1   cost:431.062154   origin: [Grp:45, GrpExpr:2]
      |        |  +--CPhysicalLimit <empty> local   rows:1   width:38  rebinds:1   cost:431.062150   origin: [Grp:45, GrpExpr:1]
      |        |     |--CPhysicalTableScan "bar" ("bar")   rows:8192   width:38  rebinds:1   cost:431.057071   origin: [Grp:1, GrpExpr:1]
      |        |     |--CScalarConst (0)   origin: [Grp:15, GrpExpr:0]
      |        |     +--CScalarConst (1)   origin: [Grp:31, GrpExpr:0]
      |        |--CScalarConst (0)   origin: [Grp:15, GrpExpr:0]
      |        +--CScalarConst (1)   origin: [Grp:31, GrpExpr:0]
      +--CScalarConst (1)   origin: [Grp:8, GrpExpr:0]
```

Translator successfully translates Plan#2 however, it throws an exception while translating
plan #1 into a `subplan` and falls back to planner.
This PR fixes this to handle the translation for plan#1.

We added a check for `COperator::EopPhysicalCorrelatedInLeftSemiNLJoin == eopid`
in `CTranslatorExprToDXL::PdxlnCorrelatedNLJoin`. This function creates a scalar subplan
if you have a correlated NL join with a true join filter. The current check only handled
`CorrelatedInnerNLJoin` case and so we extended it to handle `CorrelatedInLeftSemiNLJoin` case as well.

This produces correct subplan and there is no fallback.
```
 Gather Motion 3:1  (slice2; segments: 3)  (cost=0.00..1324032.10 rows=2 width=8)
   ->  Table Scan on foo  (cost=0.00..1324032.10 rows=1 width=8)
         Filter: a = a AND ((subplan))
         SubPlan 1
           ->  Result  (cost=0.00..431.00 rows=1 width=1)
                 ->  Materialize  (cost=0.00..431.00 rows=1 width=1)
                       ->  Broadcast Motion 3:3  (slice1; segments: 3)  (cost=0.00..431.00 rows=1 width=1)
                             ->  Table Scan on bar  (cost=0.00..431.00 rows=1 width=1)
 Settings:  optimizer=on
 Optimizer status: PQO version 2.36.0
```

1. The plan produced above can be further optimized by inserting limit
over `bar`. We will file a separate story to handle this.
2. We could not generate a repro query with NOT IN with the similar
symptom as this (-CPhysicalCorrelatedNotInLeftAntiSemiNLJoin join with
Const true filter); hence no check has been added for
`EopPhysicalCorrelatedNotInLeftAntiSemiNLJoin` join type. ORCA always
decorraltes this type of NOT IN query into CPhysicalInnerNLJoin with
scalar comparison as a <> b:
`explain select * from foo where foo.a not in (select foo.b from bar)`

Added minidump tests:

1. `CorrelatedIN-LeftSemiJoin-True.mdp` This is the repro query as shown
above.
2. `CorrelatedIN-LeftSemiNotIn-True.mdp` This was previously causing a crash with
ORCA in DEBUG build. Now it produces the correct plan.

[#147893491]
Signed-off-by: NJemish Patel <jpatel@pivotal.io>

Signed-off-by: NEkta Khanna <ekhanna@pivotal.io>

Postgres and thus (GPDB Planner) supports Values via an operator called ValueScan.
```
explain SELECT * FROM (VALUES (1, 'one'), (2, 'two'), (3, 'three')) AS t (num,letter);
                          QUERY PLAN
--------------------------------------------------------------
 Values Scan on "*VALUES*"  (cost=0.00..0.04 rows=1 width=36)
 Optimizer status: legacy query optimizer
(2 rows)
```
However, inside Orca we expand each row in the Values list into a
Result node that projects constants.
Thus the above query with three rows having 2 columns is
represented as a plan by GPORCA as an append with three Result nodes.
Each of the Result nodes is a CTG with project elements.
```
explain SELECT * FROM (VALUES (1, 'one'), (2, 'two'), (3, 'three')) AS t (num,letter);
                   QUERY PLAN
-------------------------------------------------
 Append  (cost=0.00..0.00 rows=1 width=12)
   ->  Result  (cost=0.00..0.00 rows=1 width=12)
   ->  Result  (cost=0.00..0.00 rows=1 width=12)
   ->  Result  (cost=0.00..0.00 rows=1 width=12)
 Settings:  optimizer=on
 Optimizer status: PQO version 2.32.0
(6 rows)
```

This commit introduces a new value scan operator and instead of
generating multiple result node, ORCA will now generate a value scan
node. The resulting plan will look like:

```
                                          QUERY PLAN
----------------------------------------------------------------------------------------------
 Values Scan on "Values"  (cost=0.00..0.44 rows=37000 width=4)
 Optimizer status: PQO version 2.37.0
(2 rows)
```

This enhancement bring in significant performance improvement in total
runtime of the queries involving high number of constant values.
Signed-off-by: NEkta Khanna <ekhanna@pivotal.io>

Signed-off-by: NEkta Khanna <ekhanna@pivotal.io>

* Donot generated PartOid Expression

In GPDB, PartOidExpr is not used however ORCA still generates it.
But HAWQ uses PartOid for sorting while inserting into Append Only
Row / Parquet Partitioned tables.

This patch uses Parquet Storage and Number of Partitions in a Append
Only row partitioned table to decide if PartOid should be generated.
In case of GPDB, Parquet storage is not supported and the GUC to control
the number of partitions above which sort should be used is set to int
max which is practically not feasible, so in case of GPDB PartOid expr
will never be generated, however HAWQ can control the generation of
PartOid based on the value of already existing GUCs in HAWQ.

* Remove PartOid ProjElem from minidump files

* Fixed CICGTest

* Fix CDMLTest

* Fix CDirectDispatchTest

* Fix CPhysicalParallelUnionAllTest

* Fix CCollapseProjectTest test

* Fix parser for Partition Selector

A Partition Selector node can have another partition selector node as
its immediate child. In such cases, the current parsers fails. The patch
fixes the issue

* Fix PartTbl Test

* PR Feedback Applied

* Applied HSY feedback 1
Signed-off-by: NEkta Khanna <ekhanna@pivotal.io>

* Bump ORCA to 2.37
Signed-off-by: NEkta Khanna <ekhanna@pivotal.io>

Enable GPORCA to generate better plans for non-correlated exists subquery in the WHERE clause

Consider the following exists subquery, `(select * from bar)`. GPORCA generates an elaborate count based implementation of this subquery. If bar is a fact table, the count is going to be expensive.

```
vraghavan=# explain select * from foo where foo.a = foo.b and exists (select * from bar);
                                                    QUERY PLAN
------------------------------------------------------------------------------------------------------------------
 Gather Motion 3:1  (slice3; segments: 3)  (cost=0.00..1368262.79 rows=400324 width=8)
   ->  Nested Loop  (cost=0.00..1368250.86 rows=133442 width=8)
         Join Filter: true
         ->  Table Scan on foo  (cost=0.00..461.91 rows=133442 width=8)
               Filter: a = b
         ->  Materialize  (cost=0.00..438.57 rows=1 width=1)
               ->  Broadcast Motion 1:3  (slice2)  (cost=0.00..438.57 rows=3 width=1)
                     ->  Result  (cost=0.00..438.57 rows=1 width=1)
                           Filter: (count((count()))) > 0::bigint
                           ->  Aggregate  (cost=0.00..438.57 rows=1 width=8)
                                 ->  Gather Motion 3:1  (slice1; segments: 3)  (cost=0.00..438.57 rows=1 width=8)
                                       ->  Aggregate  (cost=0.00..438.57 rows=1 width=8)
                                             ->  Table Scan on bar  (cost=0.00..437.95 rows=332395 width=1)
 Optimizer status: PQO version 2.35.1
(14 rows)
```
Planner on the other hand uses LIMIT as shown in the INIT plan.

```
vraghavan=# explain select * from foo where foo.a = foo.b and exists (select * from bar);
                                           QUERY PLAN
------------------------------------------------------------------------------------------------
 Gather Motion 3:1  (slice2; segments: 3)  (cost=0.03..13611.14 rows=1001 width=8)
   ->  Result  (cost=0.03..13611.14 rows=334 width=8)
         One-Time Filter: $0
         InitPlan  (slice3)
           ->  Limit  (cost=0.00..0.03 rows=1 width=0)
                 ->  Gather Motion 3:1  (slice1; segments: 3)  (cost=0.00..0.03 rows=1 width=0)
                       ->  Limit  (cost=0.00..0.01 rows=1 width=0)
                             ->  Seq Scan on bar  (cost=0.00..11072.84 rows=332395 width=0)
         ->  Seq Scan on foo  (cost=0.00..13611.11 rows=334 width=8)
               Filter: a = b
 Settings:  optimizer=off
 Optimizer status: legacy query optimizer
(12 rows)
```

While GPORCA doesnot support init-plan, we can nevertheless generate a better plan by using LIMIT instead of count. After this PR, GPORCA will generate the following plan with LIMIT clause.

```
vraghavan=# explain select * from foo where foo.a = foo.b and exists (select * from bar);
                                                 QUERY PLAN
------------------------------------------------------------------------------------------------------------
 Gather Motion 3:1  (slice3; segments: 3)  (cost=0.00..1368262.73 rows=400324 width=8)
   ->  Nested Loop EXISTS Join  (cost=0.00..1368250.80 rows=133442 width=8)
         Join Filter: true
         ->  Table Scan on foo  (cost=0.00..461.91 rows=133442 width=8)
               Filter: a = b
         ->  Materialize  (cost=0.00..438.57 rows=1 width=1)
               ->  Broadcast Motion 1:3  (slice2)  (cost=0.00..438.57 rows=3 width=1)
                     ->  Limit  (cost=0.00..438.57 rows=1 width=1)
                           ->  Gather Motion 3:1  (slice1; segments: 3)  (cost=0.00..438.57 rows=1 width=1)
                                 ->  Limit  (cost=0.00..438.57 rows=1 width=1)
                                       ->  Table Scan on bar  (cost=0.00..437.95 rows=332395 width=1)
 Optimizer status: PQO version 2.35.1
(12 rows)
```

Signed-off-by: NEkta Khanna <ekhanna@pivotal.io>

Each ORCA commit must BUMP the version. If the version is not
bumped new releases will not be pushed to the ORCA repository.
This commit adds the check to validate the version of the
current commit with the tag version existing on the repository.
Signed-off-by: NEkta Khanna <ekhanna@pivotal.io>

There is a tie breaker logic in FBetterThan function in CCostContext.
According to the code if the distribution is Hashed rather than Random,
it should be favored when the costs are equal.

The code was checking both if the distribution spec in the same context
is both equal to Hashed and Random which is false by default. It should
check if comparing one is Hashed and compared one is Random for correct
behavior.

There are changes to regress tests in GPDB repository, so bumping up the
minor version.

CScalarCmp and CScalarIsDistinctFrom operator must have the CScalarIdent operator
on the LHS and CScalarConst operator on the RHS. If it's
not the case the predicate is assigned a default selectivity
due to which the Cardinality estimate is impacted.

This patch fixes the issue by reordering the children of
CScalarCmp and CScalarIsDistinctFrom operator if CScalarIdent operator is on
the RHS on CScalarConst is on LHS. Also the Comparision operator is changed
due to the reordering of the arguments, if supported. If the
corresponding comparision operator does not exist or supported, the
children are not reordered.
Only cases of the type CONST = VAR are handled by this patch.
Signed-off-by: NOmer Arap <oarap@pivotal.io>

Minor cleaniup of duplicate code.

Shiny new feature in Concourse 3.3.0
(https://concourse.ci/running-tasks.html#caches)

[ci skip]

It made the assumption that it's OK to call it on a NULL pointer, which
isn't cool with all C++ compilers and options. I'm getting a bunch of
warnings like this because of it:

/home/heikki/gpdb/optimizer-main/libgpos/include/gpos/common/CDynamicPtrArray.inl:382:3: warning: nonnull argument ‘this’ compared to NULL [-Wnonnull-compare]
   if (NULL == this)
   ^~

There are a few other places that produce the same error, but one step at
a time. This is most important because it's in an inline function, so this
produces warnings also in any code that uses ORCA, like the translator code
in GPDB's src/backend/gpopt/ directory, not just ORCA itself.

Since the function is now gone, all references to it also need to be removed
from the translator code outside ORCA.

Bump up Orca version to 2.34.2

Signed-off-by: NDhanashree Kashid <dkashid@pivotal.io>

This commit introduces a check to detect if the CTE producer and
matching consumer is executed on the right place. So if CTE producer is
executed on master/segments/segment, then matching consumer also has to
execute on master/segments/segment. In rare cases, orca generates plans
that violate this assumption. This commit detects plans of that kind and
falls back.
Signed-off-by: NVenkatesh Raghavan <vraghavan@pivotal.io>
Signed-off-by: NEkta Khanna <ekhanna@pivotal.io>

The template classes in orca mostly do the implementation in
`.inl` files while some implementation also exists in `.h` files.
It makes it hard to traverse the code in .inl files since some
IDEs do not recognize formatting. Therefore this commit moves
the implementation to the `.h` files wherever is applicable.

This commit does not port implementation from `.inl` where
there exists `.cpp` implementation file as well as `.h` only has
function definitions such as `CUtils.h`.

Histogram intersection depends on the value of the bucket boundaries.
For datatypes like text, varchar, etc. Orca currently uses a hash function
to mark bucket boundaries. This function is slightly useful for equality
with singleton buckets but nothing more. So the previous join stats computation
based on histogram intersection is totally bogus. In this CL, we now modified
it into a NDV (number of distinct values) based estimation.

This reverts commit 8c315ea4.
[ci skip]

[ci skip]
Signed-off-by: NJemish Patel <jpatel@pivotal.io>

[ci skip]

Todd broke our CI in greenplum-db/gpdb@398534a9.

[ci skip]

* Make sure intent of the traceflags is clear
* Remove double negation where possible
* Update comments

Signed-off-by: NEkta Khanna <ekhanna@pivotal.io>

For a query using a correlated subselect as predicate, such as:

```
CREATE TABLE partitioned_table (a int, pk int) DISTRIBUTED BY (a)
	PARTITION BY range(pk) (end(5), end(10));
CREATE TABLE other_table (c int, d int) DISTRIBUTED BY (c);
INSERT INTO partitioned_table VALUES (1, 1), (2, 4), (3, 9);
ANALYZE ROOTPARTITION partitioned_table;

EXPLAIN SELECT pk from partitioned_table WHERE a > (SELECT d FROM other_table WHERE c = a) AND pk < 12;
```

ORCA will generate a Correlated Nested Loop Left Outer Join, which
should translate to a DXL Scan under a DXL SubPlan filter. However, the
translation happened in the following order:

0. Translate outer child (which has a filter) of correlated NLJ
0. Build a DXL SubPlan using the inner child, which is intended to serve as an
   "additional filter condition" on top of the outer child
0. Now based on the DXL plan for the outer child, we decide whether or not to
   use the additional condition (generated in #2 or #3) as a filter in the
   final result.
0. If the outer child is a Physical Sequence, we discarded the condition
   assuming that filter condition is already present in the partition
   selector.
0. This code to discard the subplan was added in
   e99325cc because, previously, we were always
   inserting additional filter as "the second child" based on the assumption
   that every DXL node has a filter child in the 2nd place. As it turned out,
   the DXL Sequence node is one counterexample: it has no filter, and it's
   second child is expected to be a partition selector.
0. We didn't catch this error in e99325cc because the test cases had a trivial
   additional filter condition of a constant true, so dropping it didn't really
   raise any eyebrows. However, the generally correct approach should be to
   retain this additional condition, either as an additional DXL Result node on
   top of the DXL for the outer child, or for appropriate types of nodes,
   inline the condition into existing filters.

This patch set fixes that.
Signed-off-by: NJemish Patel <jpatel@pivotal.io>
Signed-off-by: NEkta Khanna <ekhanna@pivotal.io>

We ensure all three cases of PdxlnCorrelatedNLJoin take ownership of the
DXLProperties object