Github user AndreSchumacher commented on a diff in the pull request:
https://github.com/apache/spark/pull/195#discussion_r11072079
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetRelation.scala ---
@@ -72,16 +71,56 @@ case class ParquetRelation(val tableName: String, val
path: String) extends Base
/** Output **/
override val output = attributes
+ /** Name (dummy value) */
+ // TODO: rethink whether ParquetRelation should inherit from BaseRelation
+ // (currently required to re-use HiveStrategies but should be removed)
+ override def tableName = "parquet"
+
// Parquet files have no concepts of keys, therefore no Partitioner
// Note: we could allow Block level access; needs to be thought through
override def isPartitioned = false
}
-object ParquetRelation {
+private[sql] object ParquetRelation {
+ // change this to enable/disable Parquet logging
+ var DEBUG: Boolean = false
+
+ def setParquetLogLevel() {
+ // Note: Parquet does not use forwarding to parent loggers which
+ // is required for the JUL-SLF4J bridge to work. Also there is
+ // a default logger that appends to Console which needs to be
+ // reset.
+ import org.slf4j.bridge.SLF4JBridgeHandler
+ import java.util.logging.Logger
+ import java.util.logging.LogManager
+
+ val loggerNames = Seq(
+ "parquet.hadoop.ColumnChunkPageWriteStore",
+ "parquet.hadoop.InternalParquetRecordWriter",
+ "parquet.hadoop.ParquetRecordReader",
+ "parquet.hadoop.ParquetInputFormat",
+ "parquet.hadoop.ParquetOutputFormat",
+ "parquet.hadoop.ParquetFileReader",
+ "parquet.hadoop.InternalParquetRecordReader",
+ "parquet.hadoop.codec.CodecConfig")
+ LogManager.getLogManager.reset()
+ SLF4JBridgeHandler.install()
+ for(name <- loggerNames) {
+ val logger = Logger.getLogger(name)
+ logger.setParent(Logger.getGlobal)
+ logger.setUseParentHandlers(true)
+ }
+ }
// The element type for the RDDs that this relation maps to.
type RowType =
org.apache.spark.sql.catalyst.expressions.GenericMutableRow
+ // The compression type
+ type CompressionType = parquet.hadoop.metadata.CompressionCodecName
+
+ // The default compression
+ val defaultCompression = CompressionCodecName.GZIP
--- End diff --
Good point, I was thinking the same but did not want to introduce lots of
Parquet dependencies on the logical plan side. Maybe there should be some Spark
system level compression types.
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