MaxGekk commented on a change in pull request #27302: [SPARK-30506][SQL][DOC] Document for generic file source options/configs URL: https://github.com/apache/spark/pull/27302#discussion_r369463516
########## File path: docs/sql-data-sources-generic-options.md ########## @@ -0,0 +1,121 @@ +--- +layout: global +title: Generic File Source Options +displayTitle: Generic File Source Options +license: | + Licensed to the Apache Software Foundation (ASF) under one or more + contributor license agreements. See the NOTICE file distributed with + this work for additional information regarding copyright ownership. + The ASF licenses this file to You under the Apache License, Version 2.0 + (the "License"); you may not use this file except in compliance with + the License. You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. +--- + +* Table of contents +{:toc} + +These generic options/configurations are effective only when using file-based sources: parquet, orc, avro, json, csv, text. + +Please note that the hierarchy of directory used in examples below is: + +{% highlight text %} + +dir1/ + ├── dir2/ + │ └── file2.parquet (schema: <file, string>, content: "file2.parquet") + └── file1.parquet (schema: <file, string>, content: "file1.parquet") + └── file3.json (schema: <file, string>, content: "{'file':'corrupt.json'}") + +{% endhighlight %} + +### Ignore Corrupt Files + +Spark allows you to use `spark.sql.files.ignoreCorruptFiles` to ignore corrupt files while reading data +from files. When set to true, the Spark jobs will continue to run when encountering corrupted files and +the contents that have been read will still be returned. + +To ignore corrupt files while reading data files, you can use: + +<div class="codetabs"> +<div data-lang="scala" markdown="1"> +{% include_example ignore_corrupt_files scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala %} +</div> + +<div data-lang="java" markdown="1"> +{% include_example ignore_corrupt_files java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java %} +</div> + +<div data-lang="python" markdown="1"> +{% include_example ignore_corrupt_files python/sql/datasource.py %} +</div> + +<div data-lang="r" markdown="1"> +{% include_example ignore_corrupt_files r/RSparkSQLExample.R %} +</div> +</div> + +### Ignore Missing Files + +Spark allows you to use `spark.sql.files.ignoreMissingFiles` to ignore missing files while reading data +from files. Here, missing file really means the deleted file under directory after you construct the +`DataFrame`. When set to true, the Spark jobs will continue to run when encountering missing files and +the contents that have been read will still be returned. + +### Path Global Filter + +`pathGlobFilter` is used to only include files with paths matching the pattern. Review comment: Looking at the implementation of `GlobFilter.accept`: ```java public boolean accept(Path path) { return pattern.matches(path.getName()) && userFilter.accept(path); } ``` the patten is applied to the final component of the path only because we pass only `filePattern` but not `userFilter`: https://github.com/apache/spark/blob/075ae1eeaf198792650287cd5b3f607a05c574bf/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningAwareFileIndex.scala#L59 So, it means for the path `/dir1/dir2/partition1/file.orc`, the pattern is applied to `file.org`, and you cannot filter by `partition1`, for instance. I think we should describe that more clearly: `with paths matching the pattern` -> `with file names matching the pattern` or more precisely `with the final component of the path matching the pattern`. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
