e79c1cde1b
### What changes were proposed in this pull request? This PR changes cache refreshing of v1 tables in v1 commands. In particular, v1 table dependents are not removed from the cache after this PR. Comparing to current implementation, we just clear cached data of all dependents and keep them in the cache. So, the next actions will fill in the cached data of the original v1 table and its dependents. In more details: 1. Modified the `CatalogImpl.refreshTable()` method to use `recacheByPlan()` instead of `lookupCachedData()`, `uncacheQuery()` and `cacheQuery()`. Users can call this method via public API like `spark.catalog.refreshTable()`. 2. Rewritten the part in `CatalogImpl.refreshTable()` which was responsible for table meta-data refreshing because this code stopped to work properly after removing of the second `sparkSession.table(tableIdent)`. 3. Added new private method `invalidateCachedTable()` to `SessionCatalog`. Comparing to the existing `SessionCatalog.refreshTable`, it invalidates the relation cache only. If we called `SessionCatalog.refreshTable` from `CatalogImpl.refreshTable()`, we would refresh temporary and global temporary views twice (that could lead to refreshing file index twice). ### Why are the changes needed? 1. This should improve user experience with table/view caching. For example, let's imagine that an user has cached v1 table and cached view based on the table. And the user passed the table to external library which drops/renames/adds partitions in the v1 table. Unfortunately, the user gets the view uncached after that even he/she hasn't uncached the view explicitly. 2. To improve code maintenance. 3. To reduce the amount of calls to Hive external catalog. 4. Also this should speed up table recaching. 5. To have the same behavior as for v2 tables supported by https://github.com/apache/spark/pull/31172 ### Does this PR introduce _any_ user-facing change? From the view of the correctness of query results, there are no behavior changes but the changes might influence on consuming memory and query execution time. For example: Before: ```scala scala> sql("CREATE TABLE tbl (c int)") scala> sql("CACHE TABLE tbl") scala> sql("CREATE VIEW v AS SELECT * FROM tbl") scala> sql("CACHE TABLE v") scala> spark.catalog.isCached("v") res6: Boolean = true scala> spark.catalog.refreshTable("tbl") scala> spark.catalog.isCached("v") res8: Boolean = false ``` After: ```scala scala> spark.catalog.refreshTable("tbl") scala> spark.catalog.isCached("v") res8: Boolean = true ``` ### How was this patch tested? 1. Added new unit tests that create a view, a temporary view and a global temporary view on top of v1/v2 tables, and refresh the base table via `ALTER TABLE .. ADD/DROP/RENAME PARTITION`. 2. By running the unified test suites: ``` $ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableAddPartitionSuite" $ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableDropPartitionSuite" # build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableRenamePartitionSuite" ``` Closes #31206 from MaxGekk/refreshTable-recache-by-plan. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> |
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css | ||
img | ||
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_config.yml | ||
building-spark.md | ||
cloud-integration.md | ||
cluster-overview.md | ||
configuration.md | ||
contributing-to-spark.md | ||
core-migration-guide.md | ||
graphx-programming-guide.md | ||
hadoop-provided.md | ||
hardware-provisioning.md | ||
index.md | ||
job-scheduling.md | ||
migration-guide.md | ||
ml-advanced.md | ||
ml-ann.md | ||
ml-classification-regression.md | ||
ml-clustering.md | ||
ml-collaborative-filtering.md | ||
ml-datasource.md | ||
ml-decision-tree.md | ||
ml-ensembles.md | ||
ml-features.md | ||
ml-frequent-pattern-mining.md | ||
ml-guide.md | ||
ml-linalg-guide.md | ||
ml-linear-methods.md | ||
ml-migration-guide.md | ||
ml-pipeline.md | ||
ml-statistics.md | ||
ml-survival-regression.md | ||
ml-tuning.md | ||
mllib-classification-regression.md | ||
mllib-clustering.md | ||
mllib-collaborative-filtering.md | ||
mllib-data-types.md | ||
mllib-decision-tree.md | ||
mllib-dimensionality-reduction.md | ||
mllib-ensembles.md | ||
mllib-evaluation-metrics.md | ||
mllib-feature-extraction.md | ||
mllib-frequent-pattern-mining.md | ||
mllib-guide.md | ||
mllib-isotonic-regression.md | ||
mllib-linear-methods.md | ||
mllib-naive-bayes.md | ||
mllib-optimization.md | ||
mllib-pmml-model-export.md | ||
mllib-statistics.md | ||
monitoring.md | ||
programming-guide.md | ||
pyspark-migration-guide.md | ||
quick-start.md | ||
rdd-programming-guide.md | ||
README.md | ||
running-on-kubernetes.md | ||
running-on-mesos.md | ||
running-on-yarn.md | ||
security.md | ||
spark-standalone.md | ||
sparkr-migration-guide.md | ||
sparkr.md | ||
sql-data-sources-avro.md | ||
sql-data-sources-binaryFile.md | ||
sql-data-sources-generic-options.md | ||
sql-data-sources-hive-tables.md | ||
sql-data-sources-jdbc.md | ||
sql-data-sources-json.md | ||
sql-data-sources-load-save-functions.md | ||
sql-data-sources-orc.md | ||
sql-data-sources-parquet.md | ||
sql-data-sources-troubleshooting.md | ||
sql-data-sources.md | ||
sql-distributed-sql-engine.md | ||
sql-getting-started.md | ||
sql-migration-guide.md | ||
sql-migration-old.md | ||
sql-performance-tuning.md | ||
sql-programming-guide.md | ||
sql-pyspark-pandas-with-arrow.md | ||
sql-ref-ansi-compliance.md | ||
sql-ref-datatypes.md | ||
sql-ref-datetime-pattern.md | ||
sql-ref-functions-builtin.md | ||
sql-ref-functions-udf-aggregate.md | ||
sql-ref-functions-udf-hive.md | ||
sql-ref-functions-udf-scalar.md | ||
sql-ref-functions.md | ||
sql-ref-identifier.md | ||
sql-ref-literals.md | ||
sql-ref-null-semantics.md | ||
sql-ref-syntax-aux-analyze-table.md | ||
sql-ref-syntax-aux-analyze.md | ||
sql-ref-syntax-aux-cache-cache-table.md | ||
sql-ref-syntax-aux-cache-clear-cache.md | ||
sql-ref-syntax-aux-cache-refresh-function.md | ||
sql-ref-syntax-aux-cache-refresh-table.md | ||
sql-ref-syntax-aux-cache-refresh.md | ||
sql-ref-syntax-aux-cache-uncache-table.md | ||
sql-ref-syntax-aux-cache.md | ||
sql-ref-syntax-aux-conf-mgmt-reset.md | ||
sql-ref-syntax-aux-conf-mgmt-set-timezone.md | ||
sql-ref-syntax-aux-conf-mgmt-set.md | ||
sql-ref-syntax-aux-conf-mgmt.md | ||
sql-ref-syntax-aux-describe-database.md | ||
sql-ref-syntax-aux-describe-function.md | ||
sql-ref-syntax-aux-describe-query.md | ||
sql-ref-syntax-aux-describe-table.md | ||
sql-ref-syntax-aux-describe.md | ||
sql-ref-syntax-aux-resource-mgmt-add-file.md | ||
sql-ref-syntax-aux-resource-mgmt-add-jar.md | ||
sql-ref-syntax-aux-resource-mgmt-list-file.md | ||
sql-ref-syntax-aux-resource-mgmt-list-jar.md | ||
sql-ref-syntax-aux-resource-mgmt.md | ||
sql-ref-syntax-aux-show-columns.md | ||
sql-ref-syntax-aux-show-create-table.md | ||
sql-ref-syntax-aux-show-databases.md | ||
sql-ref-syntax-aux-show-functions.md | ||
sql-ref-syntax-aux-show-partitions.md | ||
sql-ref-syntax-aux-show-table.md | ||
sql-ref-syntax-aux-show-tables.md | ||
sql-ref-syntax-aux-show-tblproperties.md | ||
sql-ref-syntax-aux-show-views.md | ||
sql-ref-syntax-aux-show.md | ||
sql-ref-syntax-aux.md | ||
sql-ref-syntax-ddl-alter-database.md | ||
sql-ref-syntax-ddl-alter-table.md | ||
sql-ref-syntax-ddl-alter-view.md | ||
sql-ref-syntax-ddl-create-database.md | ||
sql-ref-syntax-ddl-create-function.md | ||
sql-ref-syntax-ddl-create-table-datasource.md | ||
sql-ref-syntax-ddl-create-table-hiveformat.md | ||
sql-ref-syntax-ddl-create-table-like.md | ||
sql-ref-syntax-ddl-create-table.md | ||
sql-ref-syntax-ddl-create-view.md | ||
sql-ref-syntax-ddl-drop-database.md | ||
sql-ref-syntax-ddl-drop-function.md | ||
sql-ref-syntax-ddl-drop-table.md | ||
sql-ref-syntax-ddl-drop-view.md | ||
sql-ref-syntax-ddl-repair-table.md | ||
sql-ref-syntax-ddl-truncate-table.md | ||
sql-ref-syntax-ddl-usedb.md | ||
sql-ref-syntax-ddl.md | ||
sql-ref-syntax-dml-insert-into.md | ||
sql-ref-syntax-dml-insert-overwrite-directory-hive.md | ||
sql-ref-syntax-dml-insert-overwrite-directory.md | ||
sql-ref-syntax-dml-insert-overwrite-table.md | ||
sql-ref-syntax-dml-insert.md | ||
sql-ref-syntax-dml-load.md | ||
sql-ref-syntax-dml.md | ||
sql-ref-syntax-qry-explain.md | ||
sql-ref-syntax-qry-select-case.md | ||
sql-ref-syntax-qry-select-clusterby.md | ||
sql-ref-syntax-qry-select-cte.md | ||
sql-ref-syntax-qry-select-distribute-by.md | ||
sql-ref-syntax-qry-select-file.md | ||
sql-ref-syntax-qry-select-groupby.md | ||
sql-ref-syntax-qry-select-having.md | ||
sql-ref-syntax-qry-select-hints.md | ||
sql-ref-syntax-qry-select-inline-table.md | ||
sql-ref-syntax-qry-select-join.md | ||
sql-ref-syntax-qry-select-lateral-view.md | ||
sql-ref-syntax-qry-select-like.md | ||
sql-ref-syntax-qry-select-limit.md | ||
sql-ref-syntax-qry-select-orderby.md | ||
sql-ref-syntax-qry-select-pivot.md | ||
sql-ref-syntax-qry-select-sampling.md | ||
sql-ref-syntax-qry-select-setops.md | ||
sql-ref-syntax-qry-select-sortby.md | ||
sql-ref-syntax-qry-select-subqueries.md | ||
sql-ref-syntax-qry-select-tvf.md | ||
sql-ref-syntax-qry-select-where.md | ||
sql-ref-syntax-qry-select-window.md | ||
sql-ref-syntax-qry-select.md | ||
sql-ref-syntax-qry.md | ||
sql-ref-syntax.md | ||
sql-ref.md | ||
ss-migration-guide.md | ||
storage-openstack-swift.md | ||
streaming-custom-receivers.md | ||
streaming-kafka-0-10-integration.md | ||
streaming-kafka-integration.md | ||
streaming-kinesis-integration.md | ||
streaming-programming-guide.md | ||
structured-streaming-kafka-integration.md | ||
structured-streaming-programming-guide.md | ||
submitting-applications.md | ||
tuning.md | ||
web-ui.md |
license |
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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. |
Welcome to the Spark documentation!
This readme will walk you through navigating and building the Spark documentation, which is included here with the Spark source code. You can also find documentation specific to release versions of Spark at https://spark.apache.org/documentation.html.
Read on to learn more about viewing documentation in plain text (i.e., markdown) or building the documentation yourself. Why build it yourself? So that you have the docs that correspond to whichever version of Spark you currently have checked out of revision control.
Prerequisites
The Spark documentation build uses a number of tools to build HTML docs and API docs in Scala, Java, Python, R and SQL.
You need to have Ruby and Python installed. Also install the following libraries:
$ sudo gem install jekyll jekyll-redirect-from rouge
If your ruby version is 3.0 or higher, you should also install webrick
.
$ sudo gem install jekyll jekyll-redirect-from webrick
Note: If you are on a system with both Ruby 1.9 and Ruby 2.0 you may need to replace gem with gem2.0.
R Documentation
If you'd like to generate R documentation, you'll need to install Pandoc and install these libraries:
$ sudo Rscript -e 'install.packages(c("knitr", "devtools", "testthat", "rmarkdown"), repos="https://cloud.r-project.org/")'
$ sudo Rscript -e 'devtools::install_version("roxygen2", version = "7.1.1", repos="https://cloud.r-project.org/")'
Note: Other versions of roxygen2 might work in SparkR documentation generation but RoxygenNote
field in $SPARK_HOME/R/pkg/DESCRIPTION
is 7.1.1, which is updated if the version is mismatched.
API Documentation
To generate API docs for any language, you'll need to install these libraries:
$ sudo pip install 'sphinx<3.1.0' mkdocs numpy pydata_sphinx_theme ipython nbsphinx numpydoc
Generating the Documentation HTML
We include the Spark documentation as part of the source (as opposed to using a hosted wiki, such as the github wiki, as the definitive documentation) to enable the documentation to evolve along with the source code and be captured by revision control (currently git). This way the code automatically includes the version of the documentation that is relevant regardless of which version or release you have checked out or downloaded.
In this directory you will find text files formatted using Markdown, with an ".md" suffix. You can
read those text files directly if you want. Start with index.md
.
Execute jekyll build
from the docs/
directory to compile the site. Compiling the site with
Jekyll will create a directory called _site
containing index.html
as well as the rest of the
compiled files.
$ cd docs
$ jekyll build
You can modify the default Jekyll build as follows:
# Skip generating API docs (which takes a while)
$ SKIP_API=1 jekyll build
# Serve content locally on port 4000
$ jekyll serve --watch
# Build the site with extra features used on the live page
$ PRODUCTION=1 jekyll build
API Docs (Scaladoc, Javadoc, Sphinx, roxygen2, MkDocs)
You can build just the Spark scaladoc and javadoc by running ./build/sbt unidoc
from the $SPARK_HOME
directory.
Similarly, you can build just the PySpark docs by running make html
from the
$SPARK_HOME/python/docs
directory. Documentation is only generated for classes that are listed as
public in __init__.py
. The SparkR docs can be built by running $SPARK_HOME/R/create-docs.sh
, and
the SQL docs can be built by running $SPARK_HOME/sql/create-docs.sh
after building Spark first.
When you run jekyll build
in the docs
directory, it will also copy over the scaladoc and javadoc for the various
Spark subprojects into the docs
directory (and then also into the _site
directory). We use a
jekyll plugin to run ./build/sbt unidoc
before building the site so if you haven't run it (recently) it
may take some time as it generates all of the scaladoc and javadoc using Unidoc.
The jekyll plugin also generates the PySpark docs using Sphinx, SparkR docs
using roxygen2 and SQL docs
using MkDocs.
NOTE: To skip the step of building and copying over the Scala, Java, Python, R and SQL API docs, run SKIP_API=1 jekyll build
. In addition, SKIP_SCALADOC=1
, SKIP_PYTHONDOC=1
, SKIP_RDOC=1
and SKIP_SQLDOC=1
can be used
to skip a single step of the corresponding language. SKIP_SCALADOC
indicates skipping both the Scala and Java docs.
Automatically Rebuilding API Docs
jekyll serve --watch
will only watch what's in docs/
, and it won't follow symlinks. That means it won't monitor your API docs under python/docs
or elsewhere.
To work around this limitation for Python, install entr
and run the following in a separate shell:
cd "$SPARK_HOME/python/docs"
find .. -type f -name '*.py' \
| entr -s 'make html && cp -r _build/html/. ../../docs/api/python'
Whenever there is a change to your Python code, entr
will automatically rebuild the Python API docs and copy them to docs/
, thus triggering a Jekyll update.