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tail -f log | stdbuf -o0 awk '{print $9" "$6" - - "$7" "$18" "$19" "$20" "$11" "$12}' | sed -u "s/:[0-9]\{4,5\}//g" | sed -u "s/\(:[0-6][0-9]\)\.[0-9]\{3\}/\\1 -400/g" | logstalgia --sync --paddle-mode vhost |
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I0202 08:18:27.692706 7254 docker.cpp:614] Running docker -H unix:///var/run/docker.sock run --cpu-shares 102 --memory 536870912 -e MARATHON_APP_VERSION=2016-01-29T16:42:17.101Z -e HOST=node3.example.com -e MARATHON_APP_RESOURCE_CPUS=0.1 -e MARATHON_APP_DOCKER_IMAGE=registry.example.com/irc:e536abc322f21cf946cb9b9d0b86c1cfb2068dac -e PORT_10001=31847 -e MESOS_TASK_ID=irc.72170899-c9af-11e5-b589-02427fa617b6 -e PORT=31847 -e MARATHON_APP_RESOURCE_MEM=512.0 -e PORTS=31847 -e MARATHON_APP_RESOURCE_DISK=0.0 -e MARATHON_APP_LABELS= -e MARATHON_APP_ID=/irc -e PORT0=31847 -e MESOS_SANDBOX=/mnt/mesos/sandbox -e MESOS_CONTAINER_NAME=mesos-853e5e6e-d937-41c6-913d-48cc0a0270e3-S0.1eddc1e5-f53b-40dd-9355-e9c79c5a4044 -v /tmp/mesos/slaves/853e5e6e-d937-41c6-913d-48cc0a0270e3-S0/frameworks/3b552a3b-c098-40d6-af33-ed59ec2cd54f-0000/executors/irc.72170899-c9af-11e5-b589-02427fa617b6/runs/1eddc1e5-f53b-40dd-9355-e9c79c5a4044:/mnt/mesos/sandbox --net bridge --net=vx_0x10009 --name mesos-853e5e6e-d937-41c6-913d-48cc0a0270e3-S0 |
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{ | |
"id":"/test", | |
"instances":1, | |
"cpus":1, | |
"mem":1024, | |
"container":{ | |
"type":"DOCKER", | |
"docker":{ | |
"network":"BRIDGE", | |
"image":"ubuntu:14.04", |
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package com.trilliumstaffing.hadoop.tools | |
import java.nio.ByteBuffer | |
import org.apache.hadoop.hbase.{HBaseConfiguration, TableName} | |
import org.apache.hadoop.hbase.client._ | |
import org.apache.spark.sql.Dataset | |
import org.apache.spark.ml.linalg.{Vector, Vectors} | |
import org.apache.hadoop.hbase.protobuf.ProtobufUtil | |
import org.apache.hadoop.hbase.util.{Base64, Bytes} |
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package com.trilliumstaffing.hadoop.tools.udaf | |
import org.apache.spark.sql.expressions.{MutableAggregationBuffer, UserDefinedAggregateFunction} | |
import org.apache.spark.sql.types.{DataType, StructField, StructType} | |
import org.apache.spark.ml.linalg.SQLDataTypes.VectorType | |
import org.apache.spark.ml.linalg.{Vector, Vectors} | |
import breeze.linalg.{Vector => BV} | |
import org.apache.spark.sql.Row | |
class VectorSum extends UserDefinedAggregateFunction { |