wirybeaver commented on code in PR #15813:
URL: https://github.com/apache/pinot/pull/15813#discussion_r2093696160
##########
pinot-query-planner/src/main/java/org/apache/pinot/query/planner/physical/v2/ExchangeStrategy.java:
##########
@@ -18,50 +18,100 @@
*/
package org.apache.pinot.query.planner.physical.v2;
+import java.util.List;
+import org.apache.calcite.rel.RelDistribution;
+import org.apache.calcite.rel.RelDistributions;
+
+
/**
* Defines how data is transferred across an Exchange.
*/
public enum ExchangeStrategy {
/**
* There's a single stream in the receiver, so each stream in the sender
sends data to the same.
*/
- SINGLETON_EXCHANGE,
+ SINGLETON_EXCHANGE(false),
/**
* stream-ID X sends data to stream-ID X. This cannot be modeled by
PARTITIONING_EXCHANGE because the fan-out for
* this type of exchange is 1:1.
*/
- IDENTITY_EXCHANGE,
+ IDENTITY_EXCHANGE(false),
/**
* Each stream will partition the outgoing stream based on a set of keys and
a hash function.
* Fanout for this type of exchange is 1:all.
*/
- PARTITIONING_EXCHANGE,
+ PARTITIONING_EXCHANGE(true),
/**
* stream-ID X will sub-partition: i.e. divide the stream so that the data
is sent to the streams
* {@code X, X + F, X + 2*F, ...}. Here F is the sub-partitioning factor.
Records are assigned based on a
* hash function. This is useful when joining two tables which have
different number of partitions, but one of the
* partition counts divides the other.
* <b>Note:</b> This is different and better than partitioning exchange
because the fanout is F, and not N * (N*F).
*/
- SUB_PARTITIONING_HASH_EXCHANGE,
+ SUB_PARTITIONING_HASH_EXCHANGE(true),
/**
* Same as above but records are sub-partitioned in a round-robin way. This
will increase parallelism but lose
* data partitioning.
*/
- SUB_PARTITIONING_RR_EXCHANGE,
+ SUB_PARTITIONING_RR_EXCHANGE(false),
Review Comment:
indirect question: Could you give an example on which sql can get benefits
to use this strategy? Is it meant to be called as SUB_PARTITIONING_FANOUT?
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