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### What changes were proposed in this pull request? Add a new document page named *Generic File Source Options* for *Data Sources* menu and added following sub items: * spark.sql.files.ignoreCorruptFiles * spark.sql.files.ignoreMissingFiles * pathGlobFilter * recursiveFileLookup And here're snapshots of the generated document: <img width="1080" alt="doc-1" src="https://user-images.githubusercontent.com/16397174/73816825-87a54800-4824-11ea-97da-e5c40c59a7d4.png"> <img width="1081" alt="doc-2" src="https://user-images.githubusercontent.com/16397174/73816827-8a07a200-4824-11ea-99ec-9c8b0286625e.png"> <img width="1080" alt="doc-3" src="https://user-images.githubusercontent.com/16397174/73816831-8c69fc00-4824-11ea-84f0-6c9e94c2f0e2.png"> <img width="1081" alt="doc-4" src="https://user-images.githubusercontent.com/16397174/73816834-8f64ec80-4824-11ea-9355-76ad45476634.png"> ### Why are the changes needed? Better guidance for end-user. ### Does this PR introduce any user-facing change? No, added in Spark 3.0. ### How was this patch tested? Pass Jenkins. Closes #27302 from Ngone51/doc-generic-file-source-option. Lead-authored-by: yi.wu <yi.wu@databricks.com> Co-authored-by: Yuanjian Li <xyliyuanjian@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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| layout | title | displayTitle | license |
|---|---|---|---|
| global | Data Sources | Data Sources | 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. |
Spark SQL supports operating on a variety of data sources through the DataFrame interface. A DataFrame can be operated on using relational transformations and can also be used to create a temporary view. Registering a DataFrame as a temporary view allows you to run SQL queries over its data. This section describes the general methods for loading and saving data using the Spark Data Sources and then goes into specific options that are available for the built-in data sources.