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Posted to issues@spark.apache.org by "Brian Zhang (JIRA)" <ji...@apache.org> on 2019/08/09 21:19:00 UTC
[jira] [Created] (SPARK-28681) Spark SQL unable to read Hive ORC
table with numeric column name
Brian Zhang created SPARK-28681:
-----------------------------------
Summary: Spark SQL unable to read Hive ORC table with numeric column name
Key: SPARK-28681
URL: https://issues.apache.org/jira/browse/SPARK-28681
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.4.3
Environment: Create Hive Table:
create table table1 (`01` double) stored as orc;
insert into table table1 values(1.0);
In Spark Shell:
spark.sqlContext.sql("select * from table1");
or
spark.sqlContext.sql("select table1.`01` from table1");
it will throw following stacktrace:
org.apache.spark.sql.catalyst.parser.ParseException:
mismatched input '01' expecting \{'SELECT', 'FROM', 'ADD', 'AS', 'ALL', 'ANY', 'DISTINCT', 'WHERE', 'GROUP', 'BY', 'GROUPING', 'SETS', 'CUBE', 'ROLLUP', 'ORDER', 'HAVING', 'LIMIT', 'AT', 'OR', 'AND', 'IN', NOT, 'NO', 'EXISTS', 'BETWEEN', 'LIKE', RLIKE, 'IS', 'NULL', 'TRUE', 'FALSE', 'NULLS', 'ASC', 'DESC', 'FOR', 'INTERVAL', 'CASE', 'WHEN', 'THEN', 'ELSE', 'END', 'JOIN', 'CROSS', 'OUTER', 'INNER', 'LEFT', 'SEMI', 'RIGHT', 'FULL', 'NATURAL', 'ON', 'PIVOT', 'LATERAL', 'WINDOW', 'OVER', 'PARTITION', 'RANGE', 'ROWS', 'UNBOUNDED', 'PRECEDING', 'FOLLOWING', 'CURRENT', 'FIRST', 'AFTER', 'LAST', 'ROW', 'WITH', 'VALUES', 'CREATE', 'TABLE', 'DIRECTORY', 'VIEW', 'REPLACE', 'INSERT', 'DELETE', 'INTO', 'DESCRIBE', 'EXPLAIN', 'FORMAT', 'LOGICAL', 'CODEGEN', 'COST', 'CAST', 'SHOW', 'TABLES', 'COLUMNS', 'COLUMN', 'USE', 'PARTITIONS', 'FUNCTIONS', 'DROP', 'UNION', 'EXCEPT', 'MINUS', 'INTERSECT', 'TO', 'TABLESAMPLE', 'STRATIFY', 'ALTER', 'RENAME', 'ARRAY', 'MAP', 'STRUCT', 'COMMENT', 'SET', 'RESET', 'DATA', 'START', 'TRANSACTION', 'COMMIT', 'ROLLBACK', 'MACRO', 'IGNORE', 'BOTH', 'LEADING', 'TRAILING', 'IF', 'POSITION', 'EXTRACT', '>', 'DIV', 'PERCENT', 'BUCKET', 'OUT', 'OF', 'SORT', 'CLUSTER', 'DISTRIBUTE', 'OVERWRITE', 'TRANSFORM', 'REDUCE', 'SERDE', 'SERDEPROPERTIES', 'RECORDREADER', 'RECORDWRITER', 'DELIMITED', 'FIELDS', 'TERMINATED', 'COLLECTION', 'ITEMS', 'KEYS', 'ESCAPED', 'LINES', 'SEPARATED', 'FUNCTION', 'EXTENDED', 'REFRESH', 'CLEAR', 'CACHE', 'UNCACHE', 'LAZY', 'FORMATTED', 'GLOBAL', TEMPORARY, 'OPTIONS', 'UNSET', 'TBLPROPERTIES', 'DBPROPERTIES', 'BUCKETS', 'SKEWED', 'STORED', 'DIRECTORIES', 'LOCATION', 'EXCHANGE', 'ARCHIVE', 'UNARCHIVE', 'FILEFORMAT', 'TOUCH', 'COMPACT', 'CONCATENATE', 'CHANGE', 'CASCADE', 'RESTRICT', 'CLUSTERED', 'SORTED', 'PURGE', 'INPUTFORMAT', 'OUTPUTFORMAT', DATABASE, DATABASES, 'DFS', 'TRUNCATE', 'ANALYZE', 'COMPUTE', 'LIST', 'STATISTICS', 'PARTITIONED', 'EXTERNAL', 'DEFINED', 'REVOKE', 'GRANT', 'LOCK', 'UNLOCK', 'MSCK', 'REPAIR', 'RECOVER', 'EXPORT', 'IMPORT', 'LOAD', 'ROLE', 'ROLES', 'COMPACTIONS', 'PRINCIPALS', 'TRANSACTIONS', 'INDEX', 'INDEXES', 'LOCKS', 'OPTION', 'ANTI', 'LOCAL', 'INPATH', IDENTIFIER, BACKQUOTED_IDENTIFIER}(line 1, pos 7)
== SQL ==
struct<01:double>
-------^^^
at org.apache.spark.sql.catalyst.parser.ParseException.withCommand(ParseDriver.scala:241)
at org.apache.spark.sql.catalyst.parser.AbstractSqlParser.parse(ParseDriver.scala:117)
at org.apache.spark.sql.catalyst.parser.AbstractSqlParser.parseDataType(ParseDriver.scala:39)
at org.apache.spark.sql.execution.datasources.orc.OrcUtils$$anonfun$readSchema$1.applyOrElse(OrcUtils.scala:87)
at org.apache.spark.sql.execution.datasources.orc.OrcUtils$$anonfun$readSchema$1.applyOrElse(OrcUtils.scala:84)
at scala.collection.TraversableOnce$class.collectFirst(TraversableOnce.scala:145)
at scala.collection.AbstractIterator.collectFirst(Iterator.scala:1334)
at org.apache.spark.sql.execution.datasources.orc.OrcUtils$.readSchema(OrcUtils.scala:84)
at org.apache.spark.sql.execution.datasources.orc.OrcFileFormat.inferSchema(OrcFileFormat.scala:97)
at org.apache.spark.sql.hive.HiveMetastoreCatalog.org$apache$spark$sql$hive$HiveMetastoreCatalog$$inferIfNeeded(HiveMetastoreCatalog.scala:239)
at org.apache.spark.sql.hive.HiveMetastoreCatalog$$anonfun$6$$anonfun$7.apply(HiveMetastoreCatalog.scala:193)
at org.apache.spark.sql.hive.HiveMetastoreCatalog$$anonfun$6$$anonfun$7.apply(HiveMetastoreCatalog.scala:192)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.hive.HiveMetastoreCatalog$$anonfun$6.apply(HiveMetastoreCatalog.scala:192)
at org.apache.spark.sql.hive.HiveMetastoreCatalog$$anonfun$6.apply(HiveMetastoreCatalog.scala:185)
at org.apache.spark.sql.hive.HiveMetastoreCatalog.withTableCreationLock(HiveMetastoreCatalog.scala:54)
at org.apache.spark.sql.hive.HiveMetastoreCatalog.convertToLogicalRelation(HiveMetastoreCatalog.scala:185)
at org.apache.spark.sql.hive.RelationConversions.org$apache$spark$sql$hive$RelationConversions$$convert(HiveStrategies.scala:212)
at org.apache.spark.sql.hive.RelationConversions$$anonfun$apply$4.applyOrElse(HiveStrategies.scala:239)
at org.apache.spark.sql.hive.RelationConversions$$anonfun$apply$4.applyOrElse(HiveStrategies.scala:228)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1$$anonfun$2.apply(AnalysisHelper.scala:108)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1$$anonfun$2.apply(AnalysisHelper.scala:108)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1.apply(AnalysisHelper.scala:107)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1.apply(AnalysisHelper.scala:106)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:194)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$class.resolveOperatorsDown(AnalysisHelper.scala:106)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsDown(LogicalPlan.scala:29)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1$$anonfun$apply$6.apply(AnalysisHelper.scala:113)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1$$anonfun$apply$6.apply(AnalysisHelper.scala:113)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:326)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:324)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1.apply(AnalysisHelper.scala:113)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1.apply(AnalysisHelper.scala:106)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:194)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$class.resolveOperatorsDown(AnalysisHelper.scala:106)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsDown(LogicalPlan.scala:29)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1$$anonfun$apply$6.apply(AnalysisHelper.scala:113)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1$$anonfun$apply$6.apply(AnalysisHelper.scala:113)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:326)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:324)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1.apply(AnalysisHelper.scala:113)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsDown$1.apply(AnalysisHelper.scala:106)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:194)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$class.resolveOperatorsDown(AnalysisHelper.scala:106)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsDown(LogicalPlan.scala:29)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$class.resolveOperators(AnalysisHelper.scala:73)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:29)
at org.apache.spark.sql.hive.RelationConversions.apply(HiveStrategies.scala:228)
at org.apache.spark.sql.hive.RelationConversions.apply(HiveStrategies.scala:180)
at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:87)
at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:84)
at scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:57)
at scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:66)
at scala.collection.mutable.ArrayBuffer.foldLeft(ArrayBuffer.scala:48)
at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:84)
at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:76)
at scala.collection.immutable.List.foreach(List.scala:392)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:76)
at org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$executeSameContext(Analyzer.scala:127)
at org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:121)
at org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$executeAndCheck$1.apply(Analyzer.scala:106)
at org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$executeAndCheck$1.apply(Analyzer.scala:105)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.markInAnalyzer(AnalysisHelper.scala:201)
at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:105)
at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:57)
at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:55)
at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:47)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:79)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:642)
at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:694)
Reporter: Brian Zhang
When Hive table is stored as ORC format, and contains numeric column name. Selecting from this table via Spark SQL throws parser exception.
Setting spark.sql.hive.convertMetastoreOrc to false will be a workaround for this issue, but it has limitations as described in SPARK-22267
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