tupshin

Hadoop reduce task list for job_201207011048_0009 on 10

Killed Tasks

Task	Complete	Status	Start Time	Finish Time	Errors	Counters
task_201207011048_0009_r_000000	0.00%

2-Jul-2012 12:26:55
2-Jul-2012 12:29:32 (2mins, 37sec)
java.lang.RuntimeException: org.apache.hadoop.hive.ql.metadata.HiveException: Hive Runtime Error while processing row (tag=0) [Error getting row data with exception java.lang.ArrayIndexOutOfBoundsException: 175

tupshin

extern mod std;

use std::net::tcp::connect;
use std::net::ip::v4::parse_addr;
use std::uv::global_loop;

fn main() {
   let port:uint = 80;
	let iotask = global_loop::get();
	let ip = parse_addr("127.0.0.1");

tupshin

extern mod std;

use std::net::tcp::connect;
use std::net::tcp::write;
use std::net::ip::v4::parse_addr;
use std::uv::global_loop;

fn main() {
   let port:uint = 80;

tupshin

extern mod std;

use std::net::tcp::connect;
use std::net::tcp::write;
use std::net::ip::v4::parse_addr;
use std::uv::global_loop;

fn main() {
   let port:uint = 80;

tupshin

import java.lang.Math.sqrt

object Positioning extends App {

  class Circle(val x: Double, val y: Double, val r: Double)
  class Point(val x: Double, val y: Double)

  run_test(new Circle(-1.0, -1.0, 1.5), new Circle(1.0, 1.0, 2.0))
  run_test(new Circle(236, 67, 695.075535464), new Circle(-268, 172, 409.498473746))

tupshin

	fn send (&mut self, err: c_int, bytes: &[&[u8]]) {
		assert!(self.sender.is_some());
		let len = bytes.iter().fold(0, |l, b| { l +  b.len()});
		let header = fuse_out_header {
			len: (mem::size_of::<fuse_out_header>() + len) as u32,
			error: -err,
			unique: self.unique,
		};
		as_bytes(&header, |headerbytes| {
			let sender = self.sender.take_unwrap();

tupshin

import com.datastax.spark.connector.cql.CassandraConnector
import org.apache.spark.{SparkContext,SparkConf}
import org.apache.spark.sql.SQLContext
import com.databricks.spark.csv._
import com.datastax.spark.connector._

object CSV2Cassandra {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf(true).set("spark.cassandra.connection.host", "127.0.0.1").setMaster("local")
    val sc = new SparkContext("local", "test", conf)

tupshin

use std::io::{BufferedReader,File};
use std::collections::BinaryHeap; //latest nightlies have switch renamed PriorityQueue to BinaryHeap

fn main() {
    let n = 3u;                                            // n longest lines.
    let path = Path::new("test.txt");
    let mut file = BufferedReader::new(File::open(&path));
    let mut pq = BinaryHeap::new();                     // note: max-heap. See above about BinaryHeap

    for (i, line) in file.lines().enumerate() {

tupshin

#[repr(C, packed)] 
pub struct CqlStringMap<'a> {
  count:u16,
  map:[u8]
}

tupshin

pub type Body = [u8];
pub trait BodyBuilder{}
impl BodyBuilder for Body {}


pub struct Body2 {body:[u8]}
pub trait BodyBuilder2{}
impl BodyBuilder2 for Body2 {}

both fail with