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https://issues.apache.org/jira/browse/BEAM-12385?focusedWorklogId=606636&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-606636
]
ASF GitHub Bot logged work on BEAM-12385:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 04/Jun/21 08:07
Start Date: 04/Jun/21 08:07
Worklog Time Spent: 10m
Work Description: anantdamle commented on a change in pull request #14858:
URL: https://github.com/apache/beam/pull/14858#discussion_r644665441
##########
File path:
sdks/java/core/src/main/java/org/apache/beam/sdk/schemas/utils/AvroUtils.java
##########
@@ -906,6 +906,23 @@ private void readObject(ObjectInputStream in) throws
IOException, ClassNotFoundE
.map(x -> getFieldSchema(x.getType(), x.getName(),
namespace))
.collect(Collectors.toList()));
break;
+
+ case "NVARCHAR":
+ case "VARCHAR":
+ case "LONGNVARCHAR":
+ case "LONGVARCHAR":
+ baseType = org.apache.avro.Schema.create(Type.STRING);
Review comment:
building the Hive way into the PR.
##########
File path:
sdks/java/core/src/main/java/org/apache/beam/sdk/schemas/utils/AvroUtils.java
##########
@@ -906,6 +906,23 @@ private void readObject(ObjectInputStream in) throws
IOException, ClassNotFoundE
.map(x -> getFieldSchema(x.getType(), x.getName(),
namespace))
.collect(Collectors.toList()));
break;
+
+ case "NVARCHAR":
+ case "VARCHAR":
+ case "LONGNVARCHAR":
+ case "LONGVARCHAR":
+ baseType = org.apache.avro.Schema.create(Type.STRING);
Review comment:
@iemejia Thanks for the Hive reference. Have updated the code, also
added a small test in `SchemaUtilTest`.
##########
File path:
sdks/java/core/src/main/java/org/apache/beam/sdk/schemas/utils/AvroUtils.java
##########
@@ -1277,4 +1308,17 @@ private static void checkTypeName(Schema.TypeName got,
Schema.TypeName expected,
checkArgument(
got.equals(expected), "Can't convert '%s' to %s, expected: %s", label,
got, expected);
}
+
+ /** Helper factory to build JDBC Logical types for AVRO Schema. */
+ private static org.apache.avro.Schema makeJdbcLogicalStringAvroType(
+ Schema.LogicalType<?, ?> logicalType) {
+ JDBCType jdbcType = JDBCType.valueOf(logicalType.getIdentifier());
+ Integer size = logicalType.getArgument();
+
+ String schemaJson =
Review comment:
@RyanSkraba thanks for the suggestion, one specific reason I didn't use
the `SchemaBuilder` is due to the need to use a an Integer (non-String) value
for the property. The Schema produced by using `SchemaBuilder` looks like:
`{"type":"string","logicalType":"LONGVARCHAR","maxLength": "50"}`
vs. the expected:
`{"type":"string","logicalType":"LONGVARCHAR","maxLength": 50}`
I think its the same reason, Hive's
[TypeInfoToSchema#L116](https://github.com/apache/hive/blob/5d268834a5f5278ea76399f8af0d0ab043ae0b45/serde/src/java/org/apache/hadoop/hive/serde2/avro/TypeInfoToSchema.java#L116)
also uses the JSON based parsing approach.
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Issue Time Tracking
-------------------
Worklog Id: (was: 606636)
Time Spent: 4.5h (was: 4h 20m)
> AvroUtils exception when converting JDBC Row to GenericRecord
> -------------------------------------------------------------
>
> Key: BEAM-12385
> URL: https://issues.apache.org/jira/browse/BEAM-12385
> Project: Beam
> Issue Type: Bug
> Components: sdk-java-core
> Reporter: Anant Damle
> Assignee: Anant Damle
> Priority: P2
> Fix For: 2.31.0
>
> Time Spent: 4.5h
> Remaining Estimate: 0h
>
> `{{AvroUtils.toAvroSchema()}}` and `{{AvroUtils.toGenericRecord()}}` throw
> exception for JDBC specific logical types like: `{{DATE}}`, `{{NVARCHAR}}`,
> `{{VARCHAR}}`, `{{LONGVARCHAR}}` etc.
>
> {code:java}
> pipeline
> .apply(JdbcIO.readRows()...)
> .apply(MapElements.via(
> (Row row) -> {
> // This statement throws Exception "Unhandled Logical Type"
> org.apache.avro.Schema schema =
> AvroUtils.toAvroSchema(row.getSchema());
> }));
> {code}
>
>
> This can be handled by adding additional case-statements in AvroUtils:
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