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https://issues.apache.org/jira/browse/FLINK-8240?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16334928#comment-16334928
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ASF GitHub Bot commented on FLINK-8240:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/5240#discussion_r162947784
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/api/StreamTableEnvironment.scala
---
@@ -125,6 +129,16 @@ abstract class StreamTableEnvironment(
}
}
+ /**
+ * Creates a table from a descriptor that describes the resulting table
schema, the source
+ * connector, the source encoding, and other properties.
+ *
+ * @param schema schema descriptor describing the table to create
+ */
+ def createTable(schema: Schema): StreamTableSourceDescriptor = {
--- End diff --
See comment on `BatchTableEnvironment`
> Create unified interfaces to configure and instatiate TableSources
> ------------------------------------------------------------------
>
> Key: FLINK-8240
> URL: https://issues.apache.org/jira/browse/FLINK-8240
> Project: Flink
> Issue Type: New Feature
> Components: Table API & SQL
> Reporter: Timo Walther
> Assignee: Timo Walther
> Priority: Major
>
> At the moment every table source has different ways for configuration and
> instantiation. Some table source are tailored to a specific encoding (e.g.,
> {{KafkaAvroTableSource}}, {{KafkaJsonTableSource}}) or only support one
> encoding for reading (e.g., {{CsvTableSource}}). Each of them might implement
> a builder or support table source converters for external catalogs.
> The table sources should have a unified interface for discovery, defining
> common properties, and instantiation. The {{TableSourceConverters}} provide a
> similar functionality but use an external catalog. We might generialize this
> interface.
> In general a table source declaration depends on the following parts:
> {code}
> - Source
> - Type (e.g. Kafka, Custom)
> - Properties (e.g. topic, connection info)
> - Encoding
> - Type (e.g. Avro, JSON, CSV)
> - Schema (e.g. Avro class, JSON field names/types)
> - Rowtime descriptor/Proctime
> - Watermark strategy and Watermark properties
> - Time attribute info
> - Bucketization
> {code}
> This issue needs a design document before implementation. Any discussion is
> very welcome.
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