fonnesbeck

fonnesbeck

fonnesbeck

fonnesbeck

ramn

import java.io._

@SerialVersionUID(15L)
class Animal(name: String, age: Int) extends Serializable {
  override def toString = s"Animal($name, $age)"
}

case class Person(name: String)

// or fork := true in sbt

guyrt

#!/bin/bash
# Install sqoop and mysql connector. Store in s3 and load 
# as bootstrap step.

bucket_location='<put your bucket here>'
sqoop_jar='sqoop-1.4.3.bin__hadoop-1.0.0'
sqoop_jar_gz=$sqoop_jar.tar.gz
mysql_dir='mysql-connector-java-5.1.24'
mysql_jar='mysql-connector-java-5.1.24-bin.jar'
mysql_dir_gz=$mysql_dir.tar.gz

smougenot

  # stacktrace java as one message
  multiline {
    #type => "all" # no type means for all inputs
    pattern => "(^.+Exception: .+)|(^\s+at .+)|(^\s+... \d+ more)|(^\s*Caused by:.+)"
    what => "previous"
  }

chrishamant

#!/usr/bin/env python
"""Split large file into multiple pieces for upload to S3.

S3 only supports 5Gb files for uploading directly, so for larger CloudBioLinux
box images we need to use boto's multipart file support.

This parallelizes the task over available cores using multiprocessing.

Usage:
  s3_multipart_upload.py <file_to_transfer> <bucket_name> [<s3_key_name>]