Support to specify a shorten name for compression codec

README.md

@@ -55,7 +55,7 @@ When reading files the API accepts several options:
 * `charset`: defaults to 'UTF-8' but can be set to other valid charset names
 * `inferSchema`: automatically infers column types. It requires one extra pass over the data and is false by default
 * `comment`: skip lines beginning with this character. Default is `"#"`. Disable comments by setting this to `null`.
-* `codec`: compression codec to use when saving to file. Should be the fully qualified name of a class implementing `org.apache.hadoop.io.compress.CompressionCodec`. Defaults to no compression when a codec is not specified.
+* `codec`: compression codec to use when saving to file. Should be the fully qualified name of a class implementing `org.apache.hadoop.io.compress.CompressionCodec` or one of case-insensitive shorten names (`bzip2`, `gzip`, `lz4`, and `snappy`). Defaults to no compression when a codec is not specified.
 * `nullValue`: specificy a string that indicates a null value, any fields matching this string will be set as nulls in the DataFrame
 
 The package also support saving simple (non-nested) DataFrame. When saving you can specify the delimiter and whether we should generate a header row for the table. See following examples for more details.

src/main/scala/com/databricks/spark/csv/CsvRelation.scala

@@ -326,7 +326,7 @@ case class CsvRelation protected[spark] (
       }
       // Write the data. We assume that schema isn't changed, and we won't update it.
 
-      val codecClass = compresionCodecClass(codec)
+      val codecClass = CompressionCodecs.getCodecClass(codec)
       data.saveAsCsvFile(filesystemPath.toString, Map("delimiter" -> delimiter.toString),
         codecClass)
     } else {

src/main/scala/com/databricks/spark/csv/DefaultSource.scala

@@ -19,7 +19,7 @@ import org.apache.hadoop.fs.Path
 import org.apache.spark.sql.{DataFrame, SaveMode, SQLContext}
 import org.apache.spark.sql.sources._
 import org.apache.spark.sql.types.StructType
-import com.databricks.spark.csv.util.{ParserLibs, TextFile, TypeCast}
+import com.databricks.spark.csv.util.{CompressionCodecs, ParserLibs, TextFile, TypeCast}
 
 /**
  * Provides access to CSV data from pure SQL statements (i.e. for users of the
@@ -183,7 +183,7 @@ class DefaultSource
     }
     if (doSave) {
       // Only save data when the save mode is not ignore.
-      val codecClass = compresionCodecClass(parameters.getOrElse("codec", null))
+      val codecClass = CompressionCodecs.getCodecClass(parameters.getOrElse("codec", null))
       data.saveAsCsvFile(path, parameters, codecClass)
     }
 

src/main/scala/com/databricks/spark/csv/package.scala

@@ -26,16 +26,6 @@ package object csv {
   val defaultCsvFormat =
     CSVFormat.DEFAULT.withRecordSeparator(System.getProperty("line.separator", "\n"))
 
-  private[csv] def compresionCodecClass(className: String): Class[_ <: CompressionCodec] = {
-    className match {
-      case null => null
-      case codec =>
-        // scalastyle:off classforname
-        Class.forName(codec).asInstanceOf[Class[CompressionCodec]]
-        // scalastyle:on classforname
-    }
-  }
-
   /**
    * Adds a method, `csvFile`, to SQLContext that allows reading CSV data.
    */

src/main/scala/com/databricks/spark/csv/util/CompressionCodecs.scala

@@ -0,0 +1,49 @@
+/*
+ * Copyright 2014 Databricks
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package com.databricks.spark.csv.util
+
+import scala.util.control.Exception._
+
+import org.apache.hadoop.io.compress._
+
+private[csv] object CompressionCodecs {
+  private val shortCompressionCodecNames: Map[String, String] = {
+    val codecMap = collection.mutable.Map.empty[String, String]
+    allCatch toTry(codecMap += "bzip2" -> classOf[BZip2Codec].getName)
+    allCatch toTry(codecMap += "gzip" -> classOf[GzipCodec].getName)
+    allCatch toTry(codecMap += "lz4" -> classOf[Lz4Codec].getName)
+    allCatch toTry(codecMap += "snappy" -> classOf[SnappyCodec].getName)
+    codecMap.toMap
+  }
+
+  /**
+   * Return the codec class of the given name.
+   */
+  def getCodecClass: String => Class[_ <: CompressionCodec] = {
+    case null => null
+    case codec =>
+      val codecName = shortCompressionCodecNames.getOrElse(codec.toLowerCase, codec)
+      try {
+        // scalastyle:off classforname
+        Class.forName(codecName).asInstanceOf[Class[CompressionCodec]]
+        // scalastyle:on classforname
+      } catch {
+        case e: ClassNotFoundException =>
+          throw new IllegalArgumentException(s"Codec [$codecName] is not " +
+            s"available. Known codecs are ${shortCompressionCodecNames.keys.mkString(", ")}.")
+      }
+  }
+}

src/test/scala/com/databricks/spark/csv/CsvSuite.scala

@@ -473,6 +473,24 @@ abstract class AbstractCsvSuite extends FunSuite with BeforeAndAfterAll {
     assert(carsCopy.collect.map(_.toString).toSet == cars.collect.map(_.toString).toSet)
   }
 
+  test("Scala API save with gzip compression codec by shorten name") {
+    // Create temp directory
+    TestUtils.deleteRecursively(new File(tempEmptyDir))
+    new File(tempEmptyDir).mkdirs()
+    val copyFilePath = tempEmptyDir + "cars-copy.csv"
+
+    val cars = sqlContext.csvFile(carsFile, parserLib = parserLib)
+    cars.save("com.databricks.spark.csv", SaveMode.Overwrite,
+      Map("path" -> copyFilePath, "header" -> "true", "codec" -> "gZiP"))
+    val carsCopyPartFile = new File(copyFilePath, "part-00000.gz")
+    // Check that the part file has a .gz extension
+    assert(carsCopyPartFile.exists())
+
+    val carsCopy = sqlContext.csvFile(copyFilePath + "/")
+
+    assert(carsCopy.count == cars.count)
+    assert(carsCopy.collect.map(_.toString).toSet == cars.collect.map(_.toString).toSet)
+  }
 
   test("DSL save with quoting") {
     // Create temp directory

src/test/scala/com/databricks/spark/csv/util/CompressionCodecsSuite.scala

@@ -0,0 +1,40 @@
+/*
+ * Copyright 2014 Databricks
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package com.databricks.spark.csv.util
+
+import org.apache.hadoop.io.compress._
+import org.scalatest.FunSuite
+
+class CompressionCodecsSuite extends FunSuite {
+
+  /**
+   * Note that Lz4 codec was added from Hadoop 2.x. So, some tests might fail with
+   * class-not-found exception when Hadoop version is lower.
+   */
+  test("Get classes of compression codecs") {
+    assert(CompressionCodecs.getCodecClass(classOf[GzipCodec].getName) == classOf[GzipCodec])
+    assert(CompressionCodecs.getCodecClass(classOf[SnappyCodec].getName) == classOf[SnappyCodec])
+    assert(CompressionCodecs.getCodecClass(classOf[Lz4Codec].getName) == classOf[Lz4Codec])
+    assert(CompressionCodecs.getCodecClass(classOf[BZip2Codec].getName) == classOf[BZip2Codec])
+  }
+
+  test("Get classes of compression codecs with short names") {
+    assert(CompressionCodecs.getCodecClass("GzIp") == classOf[GzipCodec])
+    assert(CompressionCodecs.getCodecClass("Snappy") == classOf[SnappyCodec])
+    assert(CompressionCodecs.getCodecClass("lz4") == classOf[Lz4Codec])
+    assert(CompressionCodecs.getCodecClass("bZip2") == classOf[BZip2Codec])
+  }
+}

src/test/scala/com/databricks/spark/csv/util/InferSchemaSuite.scala

@@ -1,3 +1,18 @@
+/*
+ * Copyright 2014 Databricks
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
 package com.databricks.spark.csv.util
 
 import org.apache.spark.sql.types._