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The following commit(s) were added to refs/heads/master by this push: new de73753bb2e [MINOR][ML][DOCS] Fix sql data types link in the ml-pipeline page de73753bb2e is described below commit de73753bb2e5fd947f237e731ff05aa9f2711677 Author: Kent Yao <y...@apache.org> AuthorDate: Mon May 23 07:45:50 2022 -0700 [MINOR][ML][DOCS] Fix sql data types link in the ml-pipeline page ### What changes were proposed in this pull request? <img width="939" alt="image" src="https://user-images.githubusercontent.com/8326978/169767919-6c48554c-87ff-4d40-a47d-ec4da0c993f7.png"> [Spark SQL datatype reference](https://spark.apache.org/docs/latest/sql-reference.html#data-types) - `https://spark.apache.org/docs/latest/sql-reference.html#data-types` is invalid and it shall be [Spark SQL datatype reference](https://spark.apache.org/docs/latest/sql-ref-datatypes.html) - `https://spark.apache.org/docs/latest/sql-ref-datatypes.html` https://spark.apache.org/docs/latest/ml-pipeline.html#dataframe ### Why are the changes needed? doc fix ### Does this PR introduce _any_ user-facing change? no ### How was this patch tested? `bundle exec jekyll serve` Closes #36633 from yaooqinn/minor. Authored-by: Kent Yao <y...@apache.org> Signed-off-by: huaxingao <huaxin_...@apple.com> --- docs/ml-pipeline.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/ml-pipeline.md b/docs/ml-pipeline.md index 105b1273311..5f9c94781ba 100644 --- a/docs/ml-pipeline.md +++ b/docs/ml-pipeline.md @@ -72,7 +72,7 @@ E.g., a learning algorithm is an `Estimator` which trains on a `DataFrame` and p Machine learning can be applied to a wide variety of data types, such as vectors, text, images, and structured data. This API adopts the `DataFrame` from Spark SQL in order to support a variety of data types. -`DataFrame` supports many basic and structured types; see the [Spark SQL datatype reference](sql-reference.html#data-types) for a list of supported types. +`DataFrame` supports many basic and structured types; see the [Spark SQL datatype reference](sql-ref-datatypes.html) for a list of supported types. In addition to the types listed in the Spark SQL guide, `DataFrame` can use ML [`Vector`](mllib-data-types.html#local-vector) types. A `DataFrame` can be created either implicitly or explicitly from a regular `RDD`. See the code examples below and the [Spark SQL programming guide](sql-programming-guide.html) for examples. --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org