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new 495e24830ff2 [MINOR][SQL][DOCS] Fix spacing with SQL configuration
documentation
495e24830ff2 is described below
commit 495e24830ff2f7de5a295b7facedf81b9e0a2635
Author: Hyukjin Kwon <[email protected]>
AuthorDate: Wed Dec 25 12:03:24 2024 +0800
[MINOR][SQL][DOCS] Fix spacing with SQL configuration documentation
### What changes were proposed in this pull request?
This PR proposes to fix spacing with SQL configuration documentation.
### Why are the changes needed?
For correct documentation.
### Does this PR introduce _any_ user-facing change?
Trivial but yes. It affects spacing in user-facing documentation at
https://spark.apache.org/docs/latest/configuration.html.
### How was this patch tested?
Manually checked.
### Was this patch authored or co-authored using generative AI tooling?
No.
Closes #49280 from HyukjinKwon/minor-spaces.
Authored-by: Hyukjin Kwon <[email protected]>
Signed-off-by: Ruifeng Zheng <[email protected]>
---
.../org/apache/spark/sql/internal/SQLConf.scala | 46 +++++++++++-----------
.../apache/spark/sql/internal/StaticSQLConf.scala | 2 +-
2 files changed, 24 insertions(+), 24 deletions(-)
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
index be883b2112d1..d5f18231a6c1 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
@@ -257,7 +257,7 @@ object SQLConf {
"NameScope to control the visibility of names. In contrast to the
current fixed-point " +
"framework, subsequent in-tree traversals are disallowed. Most of the
fixed-point " +
"Analyzer code is reused in the form of specific node transformation
functions " +
- "(AliasResolution.resolve, FunctionResolution.resolveFunction, etc)." +
+ "(AliasResolution.resolve, FunctionResolution.resolveFunction, etc). "
+
"This feature is currently under development."
)
.version("4.0.0")
@@ -672,7 +672,7 @@ object SQLConf {
val AUTO_BROADCASTJOIN_THRESHOLD =
buildConf("spark.sql.autoBroadcastJoinThreshold")
.doc("Configures the maximum size in bytes for a table that will be
broadcast to all worker " +
- "nodes when performing a join. By setting this value to -1 broadcasting
can be disabled.")
+ "nodes when performing a join. By setting this value to -1 broadcasting
can be disabled.")
.version("1.1.0")
.bytesConf(ByteUnit.BYTE)
.createWithDefaultString("10MB")
@@ -688,7 +688,7 @@ object SQLConf {
val LIMIT_INITIAL_NUM_PARTITIONS =
buildConf("spark.sql.limit.initialNumPartitions")
.internal()
.doc("Initial number of partitions to try when executing a take on a
query. Higher values " +
- "lead to more partitions read. Lower values might lead to longer
execution times as more" +
+ "lead to more partitions read. Lower values might lead to longer
execution times as more " +
"jobs will be run")
.version("3.4.0")
.intConf
@@ -1087,8 +1087,8 @@ object SQLConf {
val FILE_COMPRESSION_FACTOR =
buildConf("spark.sql.sources.fileCompressionFactor")
.internal()
.doc("When estimating the output data size of a table scan, multiply the
file size with this " +
- "factor as the estimated data size, in case the data is compressed in
the file and lead to" +
- " a heavily underestimated result.")
+ "factor as the estimated data size, in case the data is compressed in
the file and lead to " +
+ "a heavily underestimated result.")
.version("2.3.1")
.doubleConf
.checkValue(_ > 0, "the value of fileCompressionFactor must be greater
than 0")
@@ -1340,7 +1340,7 @@ object SQLConf {
val ORC_COMPRESSION = buildConf("spark.sql.orc.compression.codec")
.doc("Sets the compression codec used when writing ORC files. If either
`compression` or " +
"`orc.compress` is specified in the table-specific options/properties,
the precedence " +
- "would be `compression`, `orc.compress`,
`spark.sql.orc.compression.codec`." +
+ "would be `compression`, `orc.compress`,
`spark.sql.orc.compression.codec`. " +
"Acceptable values include: none, uncompressed, snappy, zlib, lzo, zstd,
lz4, brotli.")
.version("2.3.0")
.stringConf
@@ -1511,7 +1511,7 @@ object SQLConf {
"to produce the partition columns instead of table scans. It applies
when all the columns " +
"scanned are partition columns and the query has an aggregate operator
that satisfies " +
"distinct semantics. By default the optimization is disabled, and
deprecated as of Spark " +
- "3.0 since it may return incorrect results when the files are empty, see
also SPARK-26709." +
+ "3.0 since it may return incorrect results when the files are empty, see
also SPARK-26709. " +
"It will be removed in the future releases. If you must use, use
'SparkSessionExtensions' " +
"instead to inject it as a custom rule.")
.version("2.1.1")
@@ -1708,7 +1708,7 @@ object SQLConf {
val V2_BUCKETING_SHUFFLE_ENABLED =
buildConf("spark.sql.sources.v2.bucketing.shuffle.enabled")
- .doc("During a storage-partitioned join, whether to allow to shuffle
only one side." +
+ .doc("During a storage-partitioned join, whether to allow to shuffle
only one side. " +
"When only one side is KeyGroupedPartitioning, if the conditions are
met, spark will " +
"only shuffle the other side. This optimization will reduce the amount
of data that " +
s"needs to be shuffle. This config requires
${V2_BUCKETING_ENABLED.key} to be enabled")
@@ -1718,9 +1718,9 @@ object SQLConf {
val V2_BUCKETING_ALLOW_JOIN_KEYS_SUBSET_OF_PARTITION_KEYS =
buildConf("spark.sql.sources.v2.bucketing.allowJoinKeysSubsetOfPartitionKeys.enabled")
- .doc("Whether to allow storage-partition join in the case where join
keys are" +
+ .doc("Whether to allow storage-partition join in the case where join
keys are " +
"a subset of the partition keys of the source tables. At planning
time, " +
- "Spark will group the partitions by only those keys that are in the
join keys." +
+ "Spark will group the partitions by only those keys that are in the
join keys. " +
s"This is currently enabled only if
${REQUIRE_ALL_CLUSTER_KEYS_FOR_DISTRIBUTION.key} " +
"is false."
)
@@ -2058,7 +2058,7 @@ object SQLConf {
val WHOLESTAGE_BROADCAST_CLEANED_SOURCE_THRESHOLD =
buildConf("spark.sql.codegen.broadcastCleanedSourceThreshold")
.internal()
- .doc("A threshold (in string length) to determine if we should make the
generated code a" +
+ .doc("A threshold (in string length) to determine if we should make the
generated code a " +
"broadcast variable in whole stage codegen. To disable this, set the
threshold to < 0; " +
"otherwise if the size is above the threshold, it'll use broadcast
variable. Note that " +
"maximum string length allowed in Java is Integer.MAX_VALUE, so
anything above it would " +
@@ -3378,7 +3378,7 @@ object SQLConf {
buildConf("spark.sql.execution.pandas.structHandlingMode")
.doc(
"The conversion mode of struct type when creating pandas DataFrame. " +
- "When \"legacy\"," +
+ "When \"legacy\", " +
"1. when Arrow optimization is disabled, convert to Row object, " +
"2. when Arrow optimization is enabled, convert to dict or raise an
Exception " +
"if there are duplicated nested field names. " +
@@ -3466,7 +3466,7 @@ object SQLConf {
buildConf("spark.sql.execution.pyspark.python")
.internal()
.doc("Python binary executable to use for PySpark in executors when
running Python " +
- "UDF, pandas UDF and pandas function APIs." +
+ "UDF, pandas UDF and pandas function APIs. " +
"If not set, it falls back to 'spark.pyspark.python' by default.")
.version("3.5.0")
.stringConf
@@ -3695,7 +3695,7 @@ object SQLConf {
val ANSI_ENABLED = buildConf(SqlApiConfHelper.ANSI_ENABLED_KEY)
.doc("When true, Spark SQL uses an ANSI compliant dialect instead of being
Hive compliant. " +
"For example, Spark will throw an exception at runtime instead of
returning null results " +
- "when the inputs to a SQL operator/function are invalid." +
+ "when the inputs to a SQL operator/function are invalid. " +
"For full details of this dialect, you can find them in the section
\"ANSI Compliance\" of " +
"Spark's documentation. Some ANSI dialect features may be not from the
ANSI SQL " +
"standard directly, but their behaviors align with ANSI SQL's style")
@@ -3786,7 +3786,7 @@ object SQLConf {
.internal()
.doc("When true, use the common expression ID for the alias when
rewriting With " +
"expressions. Otherwise, use the index of the common expression
definition. When true " +
- "this avoids duplicate alias names, but is helpful to set to false for
testing to ensure" +
+ "this avoids duplicate alias names, but is helpful to set to false for
testing to ensure " +
"that alias names are consistent.")
.version("4.0.0")
.booleanConf
@@ -4248,7 +4248,7 @@ object SQLConf {
val LEGACY_ALLOW_UNTYPED_SCALA_UDF =
buildConf("spark.sql.legacy.allowUntypedScalaUDF")
.internal()
- .doc("When set to true, user is allowed to use
org.apache.spark.sql.functions." +
+ .doc("When set to true, user is allowed to use
org.apache.spark.sql.functions. " +
"udf(f: AnyRef, dataType: DataType). Otherwise, an exception will be
thrown at runtime.")
.version("3.0.0")
.booleanConf
@@ -4285,7 +4285,7 @@ object SQLConf {
val MAX_TO_STRING_FIELDS = buildConf("spark.sql.debug.maxToStringFields")
.doc("Maximum number of fields of sequence-like entries can be converted
to strings " +
- "in debug output. Any elements beyond the limit will be dropped and
replaced by a" +
+ "in debug output. Any elements beyond the limit will be dropped and
replaced by a " +
""" "... N more fields" placeholder.""")
.version("3.0.0")
.intConf
@@ -4421,7 +4421,7 @@ object SQLConf {
val LEGACY_CTE_PRECEDENCE_POLICY =
buildConf("spark.sql.legacy.ctePrecedencePolicy")
.internal()
.doc("When LEGACY, outer CTE definitions takes precedence over inner
definitions. If set to " +
- "EXCEPTION, AnalysisException is thrown while name conflict is detected
in nested CTE." +
+ "EXCEPTION, AnalysisException is thrown while name conflict is detected
in nested CTE. " +
"The default is CORRECTED, inner CTE definitions take precedence. This
config " +
"will be removed in future versions and CORRECTED will be the only
behavior.")
.version("3.0.0")
@@ -4849,7 +4849,7 @@ object SQLConf {
.doc("When true, NULL-aware anti join execution will be planed into " +
"BroadcastHashJoinExec with flag isNullAwareAntiJoin enabled, " +
"optimized from O(M*N) calculation into O(M) calculation " +
- "using Hash lookup instead of Looping lookup." +
+ "using Hash lookup instead of Looping lookup. " +
"Only support for singleColumn NAAJ for now.")
.version("3.1.0")
.booleanConf
@@ -5241,7 +5241,7 @@ object SQLConf {
buildConf("spark.sql.legacy.raiseErrorWithoutErrorClass")
.internal()
.doc("When set to true, restores the legacy behavior of `raise_error`
and `assert_true` to " +
- "not return the `[USER_RAISED_EXCEPTION]` prefix." +
+ "not return the `[USER_RAISED_EXCEPTION]` prefix. " +
"For example, `raise_error('error!')` returns `error!` instead of " +
"`[USER_RAISED_EXCEPTION] Error!`.")
.version("4.0.0")
@@ -5299,7 +5299,7 @@ object SQLConf {
.internal()
.doc("When set to true, datetime formatter used for csv, json and xml " +
"will support zone offsets that have seconds in it. e.g. LA timezone
offset prior to 1883" +
- "was -07:52:58. When this flag is not set we lose seconds
information." )
+ " was -07:52:58. When this flag is not set we lose seconds
information." )
.version("4.0.0")
.booleanConf
.createWithDefault(true)
@@ -5380,7 +5380,7 @@ object SQLConf {
val LEGACY_BANG_EQUALS_NOT = buildConf("spark.sql.legacy.bangEqualsNot")
.internal()
.doc("When set to true, '!' is a lexical equivalent for 'NOT'. That is '!'
can be used " +
- "outside of the documented prefix usage in a logical expression." +
+ "outside of the documented prefix usage in a logical expression. " +
"Examples are: `expr ! IN (1, 2)` and `expr ! BETWEEN 1 AND 2`, but also
`IF ! EXISTS`."
)
.version("4.0.0")
@@ -5502,7 +5502,7 @@ object SQLConf {
RemovedConfig("spark.sql.legacy.compareDateTimestampInTimestamp",
"3.0.0", "true",
"It was removed to prevent errors like SPARK-23549 for non-default
value."),
RemovedConfig("spark.sql.parquet.int64AsTimestampMillis", "3.0.0",
"false",
- "The config was deprecated since Spark 2.3." +
+ "The config was deprecated since Spark 2.3. " +
s"Use '${PARQUET_OUTPUT_TIMESTAMP_TYPE.key}' instead of it."),
RemovedConfig("spark.sql.execution.pandas.respectSessionTimeZone",
"3.0.0", "true",
"The non-default behavior is considered as a bug, see SPARK-22395. " +
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/StaticSQLConf.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/StaticSQLConf.scala
index 407baba8280c..a14c584fdc6a 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/StaticSQLConf.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/StaticSQLConf.scala
@@ -280,7 +280,7 @@ object StaticSQLConf {
buildStaticConf("spark.sql.streaming.ui.enabledCustomMetricList")
.internal()
.doc("Configures a list of custom metrics on Structured Streaming UI,
which are enabled. " +
- "The list contains the name of the custom metrics separated by comma.
In aggregation" +
+ "The list contains the name of the custom metrics separated by comma.
In aggregation " +
"only sum used. The list of supported custom metrics is state store
provider specific " +
"and it can be found out for example from query progress log entry.")
.version("3.1.0")
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