refactor(obkv-hbase): migrate to user-specified schema with STRUCT types#93
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yuanoOo wants to merge 4 commits intooceanbase:mainfrom
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refactor(obkv-hbase): migrate to user-specified schema with STRUCT types#93yuanoOo wants to merge 4 commits intooceanbase:mainfrom
yuanoOo wants to merge 4 commits intooceanbase:mainfrom
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Remove cumbersome JSON schema configuration parameter and adopt Spark's
SchemaRelationProvider pattern with STRUCT types for column family mapping.
BREAKING CHANGE: The 'schema' configuration parameter has been removed.
Users must now define schemas using STRUCT types in DDL or DataFrame API.
Changes:
- Implement SchemaRelationProvider in OBKVHBaseSparkSource
- Remove schema JSON parsing logic from HBaseRelation
- Update flush() to handle STRUCT-based column family data
- Remove SCHEMA config parameter from OBKVHbaseConfig
- Update all test cases to use STRUCT approach
- Add schema validation (first field = rowkey, others = STRUCT)
Migration example:
Before:
.option("schema", "{...JSON...}")
After (DataFrame API):
val schema = StructType(Seq(
StructField("id", StringType),
StructField("cf1", StructType(Seq(
StructField("col1", StringType)
)))
))
After (Spark SQL):
CREATE TEMPORARY VIEW t (
id STRING,
cf1 STRUCT<col1: STRING>
) USING `obkv-hbase` OPTIONS(...);
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Summary
Remove cumbersome JSON schema configuration parameter and adopt Spark's SchemaRelationProvider pattern with STRUCT types for column family mapping.
BREAKING CHANGE: The 'schema' configuration parameter has been removed. Users must now define schemas using STRUCT types in DDL or DataFrame API.
Changes:
Migration example:
Before:
.option("schema", "{...JSON...}")
After (DataFrame API):
val schema = StructType(Seq( StructField("id", StringType), StructField("cf1", StructType(Seq( StructField("col1", StringType) ))) ))
After (Spark SQL):
CREATE TEMPORARY VIEW t ( id STRING,
cf1 STRUCT<col1: STRING>
) USING
obkv-hbaseOPTIONS(...);Solution Description