[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r899148598
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898894299
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898893359
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898890193
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898889007
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898886062
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898884548
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898881172
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898880354
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898878958
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898877446
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898876690
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Support raw string literal
([SPARK-36371](https://issues.apache.org/jira/browse/SPARK-36371))
+* Helper class for batch Dataset.observe()
([SPARK-34806](https://issues.apache.org/jira/browse/SPARK-34806))
+* Support specify initial partition number for rebalance
([SPARK-38410](https://issues.apache.org/jira/browse/SPARK-38410))
+* Support cascade mode for `dropNamespace` API
([SPARK-37929](https://issues.apache.org/jira/browse/SPARK-37929))
+* Allow store assignment and implicit cast among datetime types
([SPARK-37707](https://issues.apache.org/jira/browse/SPARK-37707))
+* Collect, first and last should be deterministic aggregate functions
([SPARK-32940](https://issues.apache.org/jira/browse/SPARK-32940))
+* Add ExpressionBuilder for functions with complex overloads
[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898875298
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
+* Elt() should return null if index is null under ANSI mode
([SPARK-38304](https://issues.apache.org/jira/browse/SPARK-38304))
+* Optionally return null result if element not exists in array/map
([SPARK-37750](https://issues.apache.org/jira/browse/SPARK-37750))
+* Allow casting between numeric type and timestamp type
([SPARK-37714](https://issues.apache.org/jira/browse/SPARK-37714))
+* Disable ANSI reserved keywords by default
([SPARK-37724](https://issues.apache.org/jira/browse/SPARK-37724))
+* Use store assignment rules for resolving function invocation
([SPARK-37438](https://issues.apache.org/jira/browse/SPARK-37438))
+* Add a config to allow casting between Datetime and Numeric
([SPARK-37179](https://issues.apache.org/jira/browse/SPARK-37179))
+* Add a config to optionally enforce ANSI reserved keywords
([SPARK-37133](https://issues.apache.org/jira/browse/SPARK-37133))
+* Disallow binary operations between Interval and String literal
([SPARK-36508](https://issues.apache.org/jira/browse/SPARK-36508))
+
+
+ Feature Enhancements
+
+
+
+* Support ANSI SQL INTERVAL types
([SPARK-27790](https://issues.apache.org/jira/browse/SPARK-27790))
Review Comment:
This is an umbrella too in which the last sub-tasks were done in 3.3 only.
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[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898873653
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
Review Comment:
The ticket is an umbrella for others that were merged to 3.3 in particular,
for example:
https://issues.apache.org/jira/browse/SPARK-37179
I have taken the umbrella only to not mention all sub-tasks.
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[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898824579
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
Review Comment:
After offline discussion, let me address comments directly in the PR.
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[GitHub] [spark-website] MaxGekk commented on a diff in pull request #396: Add 3.3.0 release note and news and update links
MaxGekk commented on code in PR #396:
URL: https://github.com/apache/spark-website/pull/396#discussion_r898807963
##
releases/_posts/2022-06-16-spark-release-3-3-0.md:
##
@@ -0,0 +1,477 @@
+---
+layout: post
+title: Spark Release 3.3.0
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+_edit_last: '4'
+_wpas_done_all: '1'
+---
+
+Apache Spark 3.3.0 is the fourth release of the 3.x line. With tremendous
contribution from the open-source community, this release managed to resolve in
excess of 1,600 Jira tickets.
+
+This release improve join query performance via Bloom filters, increases the
Pandas API coverage with the support of popular Pandas features such as
datetime.timedelta and merge_asof, simplifies the migration from traditional
data warehouses by improving ANSI compliance and supporting dozens of new
built-in functions, boosts development productivity with better error handling,
autocompletion, performance, and profiling.
+
+To download Apache Spark 3.3.0, visit the
[downloads](https://spark.apache.org/downloads.html) page. You can consult JIRA
for the [detailed changes](https://s.apache.org/spark-3.3.0). We have curated a
list of high level changes here, grouped by major modules.
+
+* This will become a table of contents (this text will be scraped).
+{:toc}
+
+
+### Highlight
+
+
+
+* Row-level Runtime Filtering
([SPARK-32268](https://issues.apache.org/jira/browse/SPARK-32268))
+* ANSI enhancements
([SPARK-38860](https://issues.apache.org/jira/browse/SPARK-38860))
+* Error Message Improvements
([SPARK-38781](https://issues.apache.org/jira/browse/SPARK-38781))
+* Support complex types for Parquet vectorized reader
([SPARK-34863](https://issues.apache.org/jira/browse/SPARK-34863))
+* Hidden File Metadata Support for Spark SQL
([SPARK-37273](https://issues.apache.org/jira/browse/SPARK-37273))
+* Provide a profiler for Python/Pandas UDFs
([SPARK-37443](https://issues.apache.org/jira/browse/SPARK-37443))
+* Introduce Trigger.AvailableNow for running streaming queries like
Trigger.Once in multiple batches
([SPARK-36533](https://issues.apache.org/jira/browse/SPARK-36533))
+* More comprehensive DS V2 push down capabilities
([SPARK-38788](https://issues.apache.org/jira/browse/SPARK-38788))
+* Executor Rolling in Kubernetes environment
([SPARK-37810](https://issues.apache.org/jira/browse/SPARK-37810))
+* Support Customized Kubernetes Schedulers (
[SPARK-36057](https://issues.apache.org/jira/browse/SPARK-36057))
+* Migrating from log4j 1 to log4j 2
([SPARK-37814](https://issues.apache.org/jira/browse/SPARK-37814))
+
+
+### Spark SQL and Core
+
+
+ ANSI mode
+
+
+
+* New explicit cast syntax rules in ANSI mode
([SPARK-33354](https://issues.apache.org/jira/browse/SPARK-33354))
Review Comment:
@cloud-fan Could you leave comments in
https://docs.google.com/document/d/1gGySrLGvIK8bajKdGjTI_mDqk0-YPvHmPN64YjoWfOQ/edit?usp=sharing
, please.
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