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Spark job to read gzip files, ignoring corrupted files
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import java.io._ | |
import scala.io._ | |
import java.util.zip._ | |
// Spark | |
import org.slf4j.Logger | |
import org.apache.spark.{ SparkConf, SparkContext, Logging } | |
// Hadoop | |
import org.apache.hadoop.io.compress.GzipCodec | |
object FilterBadGzipFiles extends Logging { | |
def main(args: Array[String]): Unit = { | |
val sparkConf = new SparkConf() | |
val sc = new SparkContext(sparkConf) | |
val files = sc.binaryFiles(args(0)) | |
val lines = | |
files.flatMap { | |
case (path, stream) => | |
try { | |
val is = | |
if (path.toLowerCase.endsWith(".gz")) | |
new GZIPInputStream(stream.open) | |
else | |
stream.open | |
try { | |
Source.fromInputStream(is).getLines.toList | |
} finally { | |
try { is.close } catch { case _: Throwable => } | |
} | |
} catch { | |
case e: Throwable => | |
log.warn(s"error reading from ${path}: ${e.getMessage}", e) | |
List.empty[String] | |
} | |
} | |
lines.saveAsTextFile(args(1), classOf[GzipCodec]) | |
} | |
} |
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