@@ -408,7 +408,7 @@ object SQLConf {
408408 " reduce IO and improve performance. Note, multiple continuous blocks exist in single " +
409409 s " fetch request only happen when ' ${ADAPTIVE_EXECUTION_ENABLED .key}' and " +
410410 s " ' ${REDUCE_POST_SHUFFLE_PARTITIONS_ENABLED .key}' is enabled, this feature also depends " +
411- " on a relocatable serializer, the concatenation support codec in use and the new version" +
411+ " on a relocatable serializer, the concatenation support codec in use and the new version " +
412412 " shuffle fetch protocol." )
413413 .booleanConf
414414 .createWithDefault(true )
@@ -557,7 +557,7 @@ object SQLConf {
557557 val PARQUET_INT64_AS_TIMESTAMP_MILLIS = buildConf(" spark.sql.parquet.int64AsTimestampMillis" )
558558 .doc(s " (Deprecated since Spark 2.3, please set ${PARQUET_OUTPUT_TIMESTAMP_TYPE .key}.) " +
559559 " When true, timestamp values will be stored as INT64 with TIMESTAMP_MILLIS as the " +
560- " extended type. In this mode, the microsecond portion of the timestamp value will be" +
560+ " extended type. In this mode, the microsecond portion of the timestamp value will be " +
561561 " truncated." )
562562 .booleanConf
563563 .createWithDefault(false )
@@ -638,8 +638,9 @@ object SQLConf {
638638 val PARQUET_OUTPUT_COMMITTER_CLASS = buildConf(" spark.sql.parquet.output.committer.class" )
639639 .doc(" The output committer class used by Parquet. The specified class needs to be a " +
640640 " subclass of org.apache.hadoop.mapreduce.OutputCommitter. Typically, it's also a subclass " +
641- " of org.apache.parquet.hadoop.ParquetOutputCommitter. If it is not, then metadata summaries" +
642- " will never be created, irrespective of the value of parquet.summary.metadata.level" )
641+ " of org.apache.parquet.hadoop.ParquetOutputCommitter. If it is not, then metadata " +
642+ " summaries will never be created, irrespective of the value of " +
643+ " parquet.summary.metadata.level" )
643644 .internal()
644645 .stringConf
645646 .createWithDefault(" org.apache.parquet.hadoop.ParquetOutputCommitter" )
@@ -676,7 +677,7 @@ object SQLConf {
676677 .createWithDefault(" snappy" )
677678
678679 val ORC_IMPLEMENTATION = buildConf(" spark.sql.orc.impl" )
679- .doc(" When native, use the native version of ORC support instead of the ORC library in Hive." +
680+ .doc(" When native, use the native version of ORC support instead of the ORC library in Hive. " +
680681 " It is 'hive' by default prior to Spark 2.4." )
681682 .internal()
682683 .stringConf
@@ -1225,8 +1226,8 @@ object SQLConf {
12251226 buildConf(" spark.sql.streaming.multipleWatermarkPolicy" )
12261227 .doc(" Policy to calculate the global watermark value when there are multiple watermark " +
12271228 " operators in a streaming query. The default value is 'min' which chooses " +
1228- " the minimum watermark reported across multiple operators. Other alternative value is" +
1229- " 'max' which chooses the maximum across multiple operators." +
1229+ " the minimum watermark reported across multiple operators. Other alternative value is " +
1230+ " 'max' which chooses the maximum across multiple operators. " +
12301231 " Note: This configuration cannot be changed between query restarts from the same " +
12311232 " checkpoint location." )
12321233 .stringConf
@@ -1381,7 +1382,7 @@ object SQLConf {
13811382 buildConf(" spark.sql.statistics.parallelFileListingInStatsComputation.enabled" )
13821383 .internal()
13831384 .doc(" When true, SQL commands use parallel file listing, " +
1384- " as opposed to single thread listing." +
1385+ " as opposed to single thread listing. " +
13851386 " This usually speeds up commands that need to list many directories." )
13861387 .booleanConf
13871388 .createWithDefault(true )
@@ -1702,21 +1703,21 @@ object SQLConf {
17021703
17031704 val CONCAT_BINARY_AS_STRING = buildConf(" spark.sql.function.concatBinaryAsString" )
17041705 .doc(" When this option is set to false and all inputs are binary, `functions.concat` returns " +
1705- " an output as binary. Otherwise, it returns as a string. " )
1706+ " an output as binary. Otherwise, it returns as a string." )
17061707 .booleanConf
17071708 .createWithDefault(false )
17081709
17091710 val ELT_OUTPUT_AS_STRING = buildConf(" spark.sql.function.eltOutputAsString" )
17101711 .doc(" When this option is set to false and all inputs are binary, `elt` returns " +
1711- " an output as binary. Otherwise, it returns as a string. " )
1712+ " an output as binary. Otherwise, it returns as a string." )
17121713 .booleanConf
17131714 .createWithDefault(false )
17141715
17151716 val VALIDATE_PARTITION_COLUMNS =
17161717 buildConf(" spark.sql.sources.validatePartitionColumns" )
17171718 .internal()
17181719 .doc(" When this option is set to true, partition column values will be validated with " +
1719- " user-specified schema. If the validation fails, a runtime exception is thrown." +
1720+ " user-specified schema. If the validation fails, a runtime exception is thrown. " +
17201721 " When this option is set to false, the partition column value will be converted to null " +
17211722 " if it can not be casted to corresponding user-specified schema." )
17221723 .booleanConf
@@ -2129,7 +2130,7 @@ object SQLConf {
21292130 buildConf(" spark.sql.legacy.fromDayTimeString.enabled" )
21302131 .internal()
21312132 .doc(" When true, the `from` bound is not taken into account in conversion of " +
2132- " a day-time string to an interval, and the `to` bound is used to skip" +
2133+ " a day-time string to an interval, and the `to` bound is used to skip " +
21332134 " all interval units out of the specified range. If it is set to `false`, " +
21342135 " `ParseException` is thrown if the input does not match to the pattern " +
21352136 " defined by `from` and `to`." )
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