feat: Enable UDF access to SQLTransformers#202
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Meghajit merged 3 commits intoraystack:mainraystack/dagger:mainfrom Oct 28, 2022
Shreyansh228:enable-udf-in-sqltransformerShreyansh228/dagger:enable-udf-in-sqltransformerCopy head branch name to clipboard
Merged
feat: Enable UDF access to SQLTransformers#202Meghajit merged 3 commits intoraystack:mainraystack/dagger:mainfrom Shreyansh228:enable-udf-in-sqltransformerShreyansh228/dagger:enable-udf-in-sqltransformerCopy head branch name to clipboard
Meghajit merged 3 commits intoraystack:mainraystack/dagger:mainfrom
Shreyansh228:enable-udf-in-sqltransformerShreyansh228/dagger:enable-udf-in-sqltransformerCopy head branch name to clipboard
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Currently in Dagger Flink sql-query we can access all the java and python based UDF functions. But the same UDF functions are not accessible in the post-processor(SQLTransformer). The Flink API StreamTableEnvironment instance is used to register the UDF function in method call registerFunctions() in StreamManager.java class. Since the same instance is not used to create Flink tables in SQLTransformer.java class, due to which UDFs are not accessible. We can solve this by two approaches as below. Approach-1: We can introduce the DaggerContext singleton object which holds the StreamExecutionEnvironment, StreamTableEnvironment and Configuration instance variables, we can use these variables throughout the application.This context object gets initialized only once in driver class KafkaProtoSQLProcessor.java. We can call the DaggerContext object as a static method call in the Transformer.java interface. With this DaggerContext we can register the Flink table in SQLTransformer.java. And can have access to the UDFs which were registered earlier. Approach-2: In SQLTransformer.java class we can create a new instance of StreamManager and call registerFunctions method for each SQLTransformer configuration. With this approach, if the user calls n times SqlTransformer configuration, then n times the registration of UDFs get called and n times Objects are initialized. Here we have followed Approach-1.
Meghajit
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Oct 11, 2022
dagger-common/src/main/java/io/odpf/dagger/common/core/Transformer.java
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Meghajit
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Oct 11, 2022
dagger-functions/src/main/java/io/odpf/dagger/functions/transformers/SQLTransformer.java
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KafkaProtoSQLProcessor -> StreamManager -> PostProcessorFactory -> ParentPostProcessor -> TransformProcessor and refactoring related code
Meghajit
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Oct 26, 2022
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Any reason this import been commented ?
I can see its still used in Line 50 below
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This has been un-commented and handled.
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Currently in Dagger Flink sql-query we can access all the java and python based UDF functions. But the same UDF functions are not accessible in the post-processor(SQLTransformer).
The Flink API StreamTableEnvironment instance is used to register the UDF function in method call registerFunctions() in StreamManager.java class. Since the same instance is not used to create Flink tables in SQLTransformer.java class, due to which UDFs are not accessible.
We can solve this by two approaches as below.
Approach-1:
We can introduce the DaggerContext singleton object which holds the StreamExecutionEnvironment, StreamTableEnvironment and Configuration instance variables, we can use these variables throughout the application.This context object gets initialized only once in driver class KafkaProtoSQLProcessor.java.
We can call the DaggerContext object as a static method call in the Transformer.java interface. With this DaggerContext we can register the Flink table in SQLTransformer.java. And can have access to the UDFs which were registered earlier.
Approach-2:
In SQLTransformer.java class we can create a new instance of StreamManager and call registerFunctions method for each SQLTransformer configuration. With this approach, if the user calls n times SqlTransformer configuration, then n times the registration of UDFs get called and n times Objects are initialized.
Here we have followed Approach-1.