[
https://issues.apache.org/jira/browse/FLINK-38366?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ahmad Humayun updated FLINK-38366:
----------------------------------
Description:
The following is a minimized program that causes an exception in the planner
{code:java}
from pyflink.table import EnvironmentSettings, TableEnvironment, Table
from pyflink.common import Configuration
from pyflink.table.expressions import col
cfg = Configuration()
# The program runs fine if I set any default limit
# cfg.set_string("table.exec.sort.default-limit", "10000")
settings = (
EnvironmentSettings.new_instance()
.in_batch_mode()
.with_configuration(cfg)
.build()
)
table_env = TableEnvironment.create(settings)
data = [
("Los Angeles", 9.50, "Premium", 1),
("Houston", 8.25, "Basic", 2),
("New York", 10.00, "Standard", 1),
("Chicago", 8.25, "Premium", 1)
]
source_table = table_env.from_elements(
data,
schema=["cc_city", "cc_tax_percentage", "cc_mkt_class", "extra"]
)
ordered = source_table.order_by(col('cc_city'))
result =
ordered.group_by(col('cc_tax_percentage')).select(col('cc_mkt_class').min.alias('cc_mkt_class'))
print(result.to_pandas())
{code}
The following is the exception thrown:
{code:java}
org.apache.flink.table.api.TableException: Cannot generate a valid execution
plan for the given query:
FlinkLogicalCalc(select=[EXPR$0 AS cc_mkt_class])
+- FlinkLogicalAggregate(group=[\{1}], EXPR$0=[MIN($2)])
+- FlinkLogicalSort(sort0=[$0], dir0=[ASC])
+-
FlinkLogicalTableSourceScan(table=[[*anonymous_python-input-format$1*]],
fields=[cc_city, cc_tax_percentage, cc_mkt_class, dummy])
This exception indicates that the query uses an unsupported SQL feature.
Please check the documentation for the set of currently supported SQL features.
at
org.apache.flink.table.planner.plan.optimize.program.FlinkVolcanoProgram.optimize(FlinkVolcanoProgram.scala:70)
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram.$anonfun$optimize$1(FlinkChainedProgram.scala:59)
at scala.collection.TraversableOnce$folder$1.apply(TraversableOnce.scala:196)
at scala.collection.TraversableOnce$folder$1.apply(TraversableOnce.scala:194)
at scala.collection.Iterator.foreach(Iterator.scala:943)
at scala.collection.Iterator.foreach$(Iterator.scala:943)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
at scala.collection.IterableLike.foreach(IterableLike.scala:74)
at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
at scala.collection.TraversableOnce.foldLeft(TraversableOnce.scala:199)
at scala.collection.TraversableOnce.foldLeft$(TraversableOnce.scala:192)
at scala.collection.AbstractTraversable.foldLeft(Traversable.scala:108)
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram.optimize(FlinkChainedProgram.scala:55)
at
org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.optimizeTree(BatchCommonSubGraphBasedOptimizer.scala:93)
at
org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.optimizeBlock(BatchCommonSubGraphBasedOptimizer.scala:58)
at
org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.$anonfun$doOptimize$1(BatchCommonSubGraphBasedOptimizer.scala:45)
at
org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.$anonfun$doOptimize$1$adapted(BatchCommonSubGraphBasedOptimizer.scala:45)
at scala.collection.immutable.List.foreach(List.scala:431)
at
org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.doOptimize(BatchCommonSubGraphBasedOptimizer.scala:45)
at
org.apache.flink.table.planner.plan.optimize.CommonSubGraphBasedOptimizer.optimize(CommonSubGraphBasedOptimizer.scala:87)
at
org.apache.flink.table.planner.delegation.PlannerBase.optimize(PlannerBase.scala:390)
at
org.apache.flink.table.planner.delegation.PlannerBase.getExplainGraphs(PlannerBase.scala:625)
at
org.apache.flink.table.planner.delegation.BatchPlanner.explain(BatchPlanner.scala:149)
at
org.apache.flink.table.planner.delegation.BatchPlanner.explain(BatchPlanner.scala:49)
at
org.apache.flink.table.api.internal.TableEnvironmentImpl.explainInternal(TableEnvironmentImpl.java:753)
at org.apache.flink.table.api.internal.TableImpl.explain(TableImpl.java:482)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native
Method)
at
java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77)
at
java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:569)
at
org.apache.flink.api.python.shaded.py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at
org.apache.flink.api.python.shaded.py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)
at org.apache.flink.api.python.shaded.py4j.Gateway.invoke(Gateway.java:282)
at
org.apache.flink.api.python.shaded.py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at
org.apache.flink.api.python.shaded.py4j.commands.CallCommand.execute(CallCommand.java:79)
at
org.apache.flink.api.python.shaded.py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.base/java.lang.Thread.run(Thread.java:840)
Caused by: org.apache.calcite.plan.RelOptPlanner$CannotPlanException: There are
not enough rules to produce a node with desired properties:
convention=BATCH_PHYSICAL, FlinkRelDistributionTraitDef=any, sort=[].
Missing conversions are FlinkLogicalSort[convention: LOGICAL -> BATCH_PHYSICAL,
FlinkRelDistributionTraitDef: any -> hash[1]false, sort: [0] -> [1
ASC-nulls-first]], FlinkLogicalSort[convention: LOGICAL -> BATCH_PHYSICAL,
FlinkRelDistributionTraitDef: any -> hash[1]true, sort: [0] -> [1
ASC-nulls-first]], FlinkLogicalSort[convention: LOGICAL -> BATCH_PHYSICAL,
sort: [0] -> [1 ASC-nulls-first]]
There are 3 empty subsets:
Empty subset 0: rel#240:RelSubset#5.BATCH_PHYSICAL.hash[1]false.[1
ASC-nulls-first], the relevant part of the original plan is as follows
201:FlinkLogicalSort(sort0=[$0], dir0=[ASC])
178:FlinkLogicalTableSourceScan(subset=rel#200:RelSubset#4.LOGICAL.any.[],
table=[[*anonymous_python-input-format$1*]], fields=[cc_city,
cc_tax_percentage, cc_mkt_class, dummy])
Empty subset 1: rel#215:RelSubset#5.BATCH_PHYSICAL.any.[1 ASC-nulls-first], the
relevant part of the original plan is as follows
201:FlinkLogicalSort(sort0=[$0], dir0=[ASC])
178:FlinkLogicalTableSourceScan(subset=rel#200:RelSubset#4.LOGICAL.any.[],
table=[[*anonymous_python-input-format$1*]], fields=[cc_city,
cc_tax_percentage, cc_mkt_class, dummy])
... several more lines
{code}
I don't understand why a plan cannot be generated for this program.
Furthermore, this program will run fine if I apply min on the "extra" column
instead of "cc_mkt_class". Which means its just an issue when dealing with
performing a min on a string column.
If this is not a bug, can someone explain this behaviour?
was:
The following is a minimized program that causes an exception in the planner
{code:java}
from pyflink.table import EnvironmentSettings, TableEnvironment, Table
from pyflink.common import Configuration
from pyflink.table.expressions import col
cfg = Configuration()
The program runs fine if I set any default limit
cfg.set_string("table.exec.sort.default-limit", "10000")
settings = (
EnvironmentSettings.new_instance()
.in_batch_mode()
.with_configuration(cfg)
.build()
)
table_env = TableEnvironment.create(settings)
data = [
("Los Angeles", 9.50, "Premium", 1),
("Houston", 8.25, "Basic", 2),
("New York", 10.00, "Standard", 1),
("Chicago", 8.25, "Premium", 1)
]
source_table = table_env.from_elements(
data,
schema=["cc_city", "cc_tax_percentage", "cc_mkt_class", "extra"]
)
ordered = source_table.order_by(col('cc_city'))
result =
ordered.group_by(col('cc_tax_percentage')).select(col('cc_mkt_class').min.alias('cc_mkt_class'))
print(result.to_pandas())
{code}
The following is the exception thrown:
{code:java}
org.apache.flink.table.api.TableException: Cannot generate a valid execution
plan for the given query:
FlinkLogicalCalc(select=[EXPR$0 AS cc_mkt_class])
+- FlinkLogicalAggregate(group=[\{1}], EXPR$0=[MIN($2)])
+- FlinkLogicalSort(sort0=[$0], dir0=[ASC])
+-
FlinkLogicalTableSourceScan(table=[[*anonymous_python-input-format$1*]],
fields=[cc_city, cc_tax_percentage, cc_mkt_class, dummy])
This exception indicates that the query uses an unsupported SQL feature.
Please check the documentation for the set of currently supported SQL features.
at
org.apache.flink.table.planner.plan.optimize.program.FlinkVolcanoProgram.optimize(FlinkVolcanoProgram.scala:70)
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram.$anonfun$optimize$1(FlinkChainedProgram.scala:59)
at scala.collection.TraversableOnce$folder$1.apply(TraversableOnce.scala:196)
at scala.collection.TraversableOnce$folder$1.apply(TraversableOnce.scala:194)
at scala.collection.Iterator.foreach(Iterator.scala:943)
at scala.collection.Iterator.foreach$(Iterator.scala:943)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
at scala.collection.IterableLike.foreach(IterableLike.scala:74)
at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
at scala.collection.TraversableOnce.foldLeft(TraversableOnce.scala:199)
at scala.collection.TraversableOnce.foldLeft$(TraversableOnce.scala:192)
at scala.collection.AbstractTraversable.foldLeft(Traversable.scala:108)
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram.optimize(FlinkChainedProgram.scala:55)
at
org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.optimizeTree(BatchCommonSubGraphBasedOptimizer.scala:93)
at
org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.optimizeBlock(BatchCommonSubGraphBasedOptimizer.scala:58)
at
org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.$anonfun$doOptimize$1(BatchCommonSubGraphBasedOptimizer.scala:45)
at
org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.$anonfun$doOptimize$1$adapted(BatchCommonSubGraphBasedOptimizer.scala:45)
at scala.collection.immutable.List.foreach(List.scala:431)
at
org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.doOptimize(BatchCommonSubGraphBasedOptimizer.scala:45)
at
org.apache.flink.table.planner.plan.optimize.CommonSubGraphBasedOptimizer.optimize(CommonSubGraphBasedOptimizer.scala:87)
at
org.apache.flink.table.planner.delegation.PlannerBase.optimize(PlannerBase.scala:390)
at
org.apache.flink.table.planner.delegation.PlannerBase.getExplainGraphs(PlannerBase.scala:625)
at
org.apache.flink.table.planner.delegation.BatchPlanner.explain(BatchPlanner.scala:149)
at
org.apache.flink.table.planner.delegation.BatchPlanner.explain(BatchPlanner.scala:49)
at
org.apache.flink.table.api.internal.TableEnvironmentImpl.explainInternal(TableEnvironmentImpl.java:753)
at org.apache.flink.table.api.internal.TableImpl.explain(TableImpl.java:482)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native
Method)
at
java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77)
at
java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:569)
at
org.apache.flink.api.python.shaded.py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at
org.apache.flink.api.python.shaded.py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)
at org.apache.flink.api.python.shaded.py4j.Gateway.invoke(Gateway.java:282)
at
org.apache.flink.api.python.shaded.py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at
org.apache.flink.api.python.shaded.py4j.commands.CallCommand.execute(CallCommand.java:79)
at
org.apache.flink.api.python.shaded.py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.base/java.lang.Thread.run(Thread.java:840)
Caused by: org.apache.calcite.plan.RelOptPlanner$CannotPlanException: There are
not enough rules to produce a node with desired properties:
convention=BATCH_PHYSICAL, FlinkRelDistributionTraitDef=any, sort=[].
Missing conversions are FlinkLogicalSort[convention: LOGICAL -> BATCH_PHYSICAL,
FlinkRelDistributionTraitDef: any -> hash[1]false, sort: [0] -> [1
ASC-nulls-first]], FlinkLogicalSort[convention: LOGICAL -> BATCH_PHYSICAL,
FlinkRelDistributionTraitDef: any -> hash[1]true, sort: [0] -> [1
ASC-nulls-first]], FlinkLogicalSort[convention: LOGICAL -> BATCH_PHYSICAL,
sort: [0] -> [1 ASC-nulls-first]]
There are 3 empty subsets:
Empty subset 0: rel#240:RelSubset#5.BATCH_PHYSICAL.hash[1]false.[1
ASC-nulls-first], the relevant part of the original plan is as follows
201:FlinkLogicalSort(sort0=[$0], dir0=[ASC])
178:FlinkLogicalTableSourceScan(subset=rel#200:RelSubset#4.LOGICAL.any.[],
table=[[*anonymous_python-input-format$1*]], fields=[cc_city,
cc_tax_percentage, cc_mkt_class, dummy])
Empty subset 1: rel#215:RelSubset#5.BATCH_PHYSICAL.any.[1 ASC-nulls-first], the
relevant part of the original plan is as follows
201:FlinkLogicalSort(sort0=[$0], dir0=[ASC])
178:FlinkLogicalTableSourceScan(subset=rel#200:RelSubset#4.LOGICAL.any.[],
table=[[*anonymous_python-input-format$1*]], fields=[cc_city,
cc_tax_percentage, cc_mkt_class, dummy])
... several more lines
{code}
I don't understand why a plan cannot be generated for this program.
Furthermore, this program will run fine if I apply min on the "extra" column
instead of "cc_mkt_class". Which means its just an issue when dealing with
performing a min on a string column.
If this is not a bug, can someone explain this behaviour?
> Pyflink planner throws exception in batch mode when there is no limit on
> order_by()
> -----------------------------------------------------------------------------------
>
> Key: FLINK-38366
> URL: https://issues.apache.org/jira/browse/FLINK-38366
> Project: Flink
> Issue Type: Bug
> Components: Table SQL / Planner
> Affects Versions: 2.0.0
> Environment: Pyflink 2.0.0
> Reporter: Ahmad Humayun
> Priority: Major
>
> The following is a minimized program that causes an exception in the planner
> {code:java}
> from pyflink.table import EnvironmentSettings, TableEnvironment, Table
> from pyflink.common import Configuration
> from pyflink.table.expressions import col
>
> cfg = Configuration()
> # The program runs fine if I set any default limit
> # cfg.set_string("table.exec.sort.default-limit", "10000")
>
> settings = (
> EnvironmentSettings.new_instance()
> .in_batch_mode()
> .with_configuration(cfg)
> .build()
> )
>
> table_env = TableEnvironment.create(settings)
>
> data = [
> ("Los Angeles", 9.50, "Premium", 1),
> ("Houston", 8.25, "Basic", 2),
> ("New York", 10.00, "Standard", 1),
> ("Chicago", 8.25, "Premium", 1)
> ]
>
> source_table = table_env.from_elements(
> data,
> schema=["cc_city", "cc_tax_percentage", "cc_mkt_class", "extra"]
> )
>
> ordered = source_table.order_by(col('cc_city'))
> result =
> ordered.group_by(col('cc_tax_percentage')).select(col('cc_mkt_class').min.alias('cc_mkt_class'))
>
> print(result.to_pandas())
> {code}
>
>
> The following is the exception thrown:
>
>
> {code:java}
> org.apache.flink.table.api.TableException: Cannot generate a valid execution
> plan for the given query:
>
> FlinkLogicalCalc(select=[EXPR$0 AS cc_mkt_class])
> +- FlinkLogicalAggregate(group=[\{1}], EXPR$0=[MIN($2)])
> +- FlinkLogicalSort(sort0=[$0], dir0=[ASC])
> +-
> FlinkLogicalTableSourceScan(table=[[*anonymous_python-input-format$1*]],
> fields=[cc_city, cc_tax_percentage, cc_mkt_class, dummy])
>
> This exception indicates that the query uses an unsupported SQL feature.
> Please check the documentation for the set of currently supported SQL
> features.
> at
> org.apache.flink.table.planner.plan.optimize.program.FlinkVolcanoProgram.optimize(FlinkVolcanoProgram.scala:70)
> at
> org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram.$anonfun$optimize$1(FlinkChainedProgram.scala:59)
> at
> scala.collection.TraversableOnce$folder$1.apply(TraversableOnce.scala:196)
> at
> scala.collection.TraversableOnce$folder$1.apply(TraversableOnce.scala:194)
> at scala.collection.Iterator.foreach(Iterator.scala:943)
> at scala.collection.Iterator.foreach$(Iterator.scala:943)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
> at scala.collection.IterableLike.foreach(IterableLike.scala:74)
> at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
> at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
> at scala.collection.TraversableOnce.foldLeft(TraversableOnce.scala:199)
> at scala.collection.TraversableOnce.foldLeft$(TraversableOnce.scala:192)
> at scala.collection.AbstractTraversable.foldLeft(Traversable.scala:108)
> at
> org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram.optimize(FlinkChainedProgram.scala:55)
> at
> org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.optimizeTree(BatchCommonSubGraphBasedOptimizer.scala:93)
> at
> org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.optimizeBlock(BatchCommonSubGraphBasedOptimizer.scala:58)
> at
> org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.$anonfun$doOptimize$1(BatchCommonSubGraphBasedOptimizer.scala:45)
> at
> org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.$anonfun$doOptimize$1$adapted(BatchCommonSubGraphBasedOptimizer.scala:45)
> at scala.collection.immutable.List.foreach(List.scala:431)
> at
> org.apache.flink.table.planner.plan.optimize.BatchCommonSubGraphBasedOptimizer.doOptimize(BatchCommonSubGraphBasedOptimizer.scala:45)
> at
> org.apache.flink.table.planner.plan.optimize.CommonSubGraphBasedOptimizer.optimize(CommonSubGraphBasedOptimizer.scala:87)
> at
> org.apache.flink.table.planner.delegation.PlannerBase.optimize(PlannerBase.scala:390)
> at
> org.apache.flink.table.planner.delegation.PlannerBase.getExplainGraphs(PlannerBase.scala:625)
> at
> org.apache.flink.table.planner.delegation.BatchPlanner.explain(BatchPlanner.scala:149)
> at
> org.apache.flink.table.planner.delegation.BatchPlanner.explain(BatchPlanner.scala:49)
> at
> org.apache.flink.table.api.internal.TableEnvironmentImpl.explainInternal(TableEnvironmentImpl.java:753)
> at
> org.apache.flink.table.api.internal.TableImpl.explain(TableImpl.java:482)
> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native
> Method)
> at
> java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77)
> at
> java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.base/java.lang.reflect.Method.invoke(Method.java:569)
> at
> org.apache.flink.api.python.shaded.py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
> at
> org.apache.flink.api.python.shaded.py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)
> at org.apache.flink.api.python.shaded.py4j.Gateway.invoke(Gateway.java:282)
> at
> org.apache.flink.api.python.shaded.py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> at
> org.apache.flink.api.python.shaded.py4j.commands.CallCommand.execute(CallCommand.java:79)
> at
> org.apache.flink.api.python.shaded.py4j.GatewayConnection.run(GatewayConnection.java:238)
> at java.base/java.lang.Thread.run(Thread.java:840)
> Caused by: org.apache.calcite.plan.RelOptPlanner$CannotPlanException: There
> are not enough rules to produce a node with desired properties:
> convention=BATCH_PHYSICAL, FlinkRelDistributionTraitDef=any, sort=[].
> Missing conversions are FlinkLogicalSort[convention: LOGICAL ->
> BATCH_PHYSICAL, FlinkRelDistributionTraitDef: any -> hash[1]false, sort: [0]
> -> [1 ASC-nulls-first]], FlinkLogicalSort[convention: LOGICAL ->
> BATCH_PHYSICAL, FlinkRelDistributionTraitDef: any -> hash[1]true, sort: [0]
> -> [1 ASC-nulls-first]], FlinkLogicalSort[convention: LOGICAL ->
> BATCH_PHYSICAL, sort: [0] -> [1 ASC-nulls-first]]
> There are 3 empty subsets:
> Empty subset 0: rel#240:RelSubset#5.BATCH_PHYSICAL.hash[1]false.[1
> ASC-nulls-first], the relevant part of the original plan is as follows
> 201:FlinkLogicalSort(sort0=[$0], dir0=[ASC])
> 178:FlinkLogicalTableSourceScan(subset=rel#200:RelSubset#4.LOGICAL.any.[],
> table=[[*anonymous_python-input-format$1*]], fields=[cc_city,
> cc_tax_percentage, cc_mkt_class, dummy])
>
> Empty subset 1: rel#215:RelSubset#5.BATCH_PHYSICAL.any.[1 ASC-nulls-first],
> the relevant part of the original plan is as follows
> 201:FlinkLogicalSort(sort0=[$0], dir0=[ASC])
> 178:FlinkLogicalTableSourceScan(subset=rel#200:RelSubset#4.LOGICAL.any.[],
> table=[[*anonymous_python-input-format$1*]], fields=[cc_city,
> cc_tax_percentage, cc_mkt_class, dummy])
> ... several more lines
> {code}
> I don't understand why a plan cannot be generated for this program.
> Furthermore, this program will run fine if I apply min on the "extra" column
> instead of "cc_mkt_class". Which means its just an issue when dealing with
> performing a min on a string column.
> If this is not a bug, can someone explain this behaviour?
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