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### What changes were proposed in this pull request? Currently, there is no migration section for PySpark, SparkCore and Structured Streaming. It is difficult for users to know what to do when they upgrade. This PR proposes to create create a "Migration Guide" tap at Spark documentation.   This page will contain migration guides for Spark SQL, PySpark, SparkR, MLlib, Structured Streaming and Core. Basically it is a refactoring. There are some new information added, which I will leave a comment inlined for easier review. 1. **MLlib** Merge [ml-guide.html#migration-guide](https://spark.apache.org/docs/latest/ml-guide.html#migration-guide) and [ml-migration-guides.html](https://spark.apache.org/docs/latest/ml-migration-guides.html) ``` 'docs/ml-guide.md' ↓ Merge new/old migration guides 'docs/ml-migration-guide.md' ``` 2. **PySpark** Extract PySpark specific items from https://spark.apache.org/docs/latest/sql-migration-guide-upgrade.html ``` 'docs/sql-migration-guide-upgrade.md' ↓ Extract PySpark specific items 'docs/pyspark-migration-guide.md' ``` 3. **SparkR** Move [sparkr.html#migration-guide](https://spark.apache.org/docs/latest/sparkr.html#migration-guide) into a separate file, and extract from [sql-migration-guide-upgrade.html](https://spark.apache.org/docs/latest/sql-migration-guide-upgrade.html) ``` 'docs/sparkr.md' 'docs/sql-migration-guide-upgrade.md' Move migration guide section ↘ ↙ Extract SparkR specific items docs/sparkr-migration-guide.md ``` 4. **Core** Newly created at `'docs/core-migration-guide.md'`. I skimmed resolved JIRAs at 3.0.0 and found some items to note. 5. **Structured Streaming** Newly created at `'docs/ss-migration-guide.md'`. I skimmed resolved JIRAs at 3.0.0 and found some items to note. 6. **SQL** Merged [sql-migration-guide-upgrade.html](https://spark.apache.org/docs/latest/sql-migration-guide-upgrade.html) and [sql-migration-guide-hive-compatibility.html](https://spark.apache.org/docs/latest/sql-migration-guide-hive-compatibility.html) ``` 'docs/sql-migration-guide-hive-compatibility.md' 'docs/sql-migration-guide-upgrade.md' Move Hive compatibility section ↘ ↙ Left over after filtering PySpark and SparkR items 'docs/sql-migration-guide.md' ``` ### Why are the changes needed? In order for users in production to effectively migrate to higher versions, and detect behaviour or breaking changes before upgrading and/or migrating. ### Does this PR introduce any user-facing change? Yes, this changes Spark's documentation at https://spark.apache.org/docs/latest/index.html. ### How was this patch tested? Manually build the doc. This can be verified as below: ```bash cd docs SKIP_API=1 jekyll build open _site/index.html ``` Closes #25757 from HyukjinKwon/migration-doc. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
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| layout | title | displayTitle | license |
|---|---|---|---|
| global | Migration Guide: Structured Streaming | Migration Guide: Structured Streaming | 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}
Note that this migration guide describes the items specific to Structured Streaming. Many items of SQL migration can be applied when migrating Structured Streaming to higher versions. Please refer Migration Guide: SQL, Datasets and DataFrame.
Upgrading from Structured Streaming 2.4 to 3.0
- In Spark 3.0, Structured Streaming forces the source schema into nullable when file-based datasources such as text, json, csv, parquet and orc are used via
spark.readStream(...). Previously, it respected the nullability in source schema; however, it caused issues tricky to debug with NPE. To restore the previous behavior, setspark.sql.streaming.fileSource.schema.forceNullabletofalse.