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https://issues.apache.org/jira/browse/BEAM-4461?focusedWorklogId=205959&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-205959
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ASF GitHub Bot logged work on BEAM-4461:
----------------------------------------
Author: ASF GitHub Bot
Created on: 28/Feb/19 19:10
Start Date: 28/Feb/19 19:10
Worklog Time Spent: 10m
Work Description: reuvenlax commented on pull request #7353: [BEAM-4461]
Support inner and outer style joins in CoGroup.
URL: https://github.com/apache/beam/pull/7353#discussion_r261341533
##########
File path:
sdks/java/core/src/main/java/org/apache/beam/sdk/schemas/transforms/CoGroup.java
##########
@@ -107,156 +105,241 @@
* those fields match. In this case, fields must be specified for every input
PCollection. For
* example:
*
- * <pre>{@code PCollection<KV<Row, Row>> joined = PCollectionTuple
- * .of(input1Tag, input1)
- * .and(input2Tag, input2)
+ * <pre>{@code PCollection<KV<Row, Row>> joined
+ * = PCollectionTuple.of("input1Tag", input1, "input2Tag", input2)
* .apply(CoGroup
- * .byFieldNames(input1Tag, "referringUser"))
- * .byFieldNames(input2Tag, "user"));
+ * .join("input1Tag", By.fieldNames("referringUser")))
+ * .join("input2Tag", By.fieldNames("user")));
* }</pre>
+ *
+ * <p>Traditional (SQL) joins are cross-product joins. All rows that match the
join condition are
+ * combined into individual rows and returned; in fact any SQL inner joins is
a subset of the
+ * cross-product of two tables. This transform also supports the same
functionality using the {@link
+ * Inner#crossProductJoin()} method.
+ *
+ * <p>For example, consider the SQL join: SELECT * FROM input1 INNER JOIN
input2 ON input1.user =
+ * input2.user
+ *
+ * <p>You could express this with:
+ *
+ * <pre>{@code
+ * PCollection<Row> joined = PCollectionTuple.of("input1", input1, "input2",
input2)
+ * .apply(CoGroup.join(By.fieldNames("user")).crossProductJoin();
+ * }</pre>
+ *
+ * <p>The schema of the output PCollection contains a nested message for each
of input1 and input2.
+ * Like above, you could use the {@link Convert} transform to convert it to
the following POJO:
+ *
+ * <pre>{@code
+ * {@literal @}DefaultSchema(JavaFieldSchema.class)
+ * public class JoinedValue {
+ * public Input1Type input1;
+ * public Input2Type input2;
+ * }
+ * }</pre>
+ *
+ * <p>The {@link Unnest} transform can then be used to flatten all the
subfields into one single
+ * top-level row containing all the fields in both Input1 and Input2; this
will often be combined
+ * with a {@link Select} transform to select out the fields of interest, as
the key fields will be
+ * identical between input1 and input2.
+ *
+ * <p>This transform also supports outer-join semantics. By default, all input
PCollections must
+ * participate fully in the join, providing inner-join semantics. This means
that if if all input
Review comment:
fixed
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Issue Time Tracking
-------------------
Worklog Id: (was: 205959)
Time Spent: 21h 40m (was: 21.5h)
> Create a library of useful transforms that use schemas
> ------------------------------------------------------
>
> Key: BEAM-4461
> URL: https://issues.apache.org/jira/browse/BEAM-4461
> Project: Beam
> Issue Type: Sub-task
> Components: sdk-java-core
> Reporter: Reuven Lax
> Assignee: Reuven Lax
> Priority: Major
> Labels: triaged
> Time Spent: 21h 40m
> Remaining Estimate: 0h
>
> e.g. JoinBy(fields). Project, Filter, etc.
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