Github user ahmed-mahran commented on a diff in the pull request:
https://github.com/apache/spark/pull/14234#discussion_r71073763
--- Diff: docs/structured-streaming-programming-guide.md ---
@@ -519,10 +502,10 @@ csvDF = spark \
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-These examples generate streaming DataFrames that are untyped, meaning
that the schema of the DataFrame is not checked at compile time, only checked
at runtime when the query is submitted. Some operations like `map`, `flatMap`,
etc. need the type to be known at compile time. To do those, you can convert
these untyped streaming DataFrames to typed streaming Datasets using the same
methods as static DataFrame. See the SQL Programming Guide for more details.
Additionally, more details on the supported streaming sources are discussed
later in the document.
--- End diff --
Added link `[SQL Programming Guide](sql-programming-guide.html)`
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