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From jane thorpe <janethor...@aol.com.INVALID>
Subject Re: HDFS file hdfs://127.0.0.1:9000/hdfs/spark/examples/README.txt
Date Tue, 07 Apr 2020 04:12:14 GMT

Hi Som,

HdfsWordCount program  counts words 
>From files you place in a  directory with the name of argv [args.length -1]  while the
program is running in a for (;;)  loop until user press CTRL C. 

Why  does program name  have prefix of  HDFS   ? 
HADOOP distributed  FileSystem.

Is it a program which demonstrates 
HDFS  or  streaming.

I am really really  confused  with this  program ExceptionHandlingTest.

What exception handling is being tested,  JVM's throw new exception  syntax , if value greater
than  0.75, 
 or is it some thing meant to be testing SPARK API exception handling.


spark.sparkContext.parallelize(0 until spark.sparkContext.defaultParallelism).foreach    

    {
             i => if (math.random > 0.75)
            { 
                  throw new Exception("Testing exception handling") 
           }
 }


package org.apache.spark.examples

 import org.apache.spark.sql.SparkSession

 object ExceptionHandlingTest
 { 
def main(args: Array[String]): Unit =
 { 
val spark = SparkSession .builder .appName("ExceptionHandlingTest") .getOrCreate()

 spark.sparkContext.parallelize(0 until spark.sparkContext.defaultParallelism).foreach {
 i => if (math.random > 0.75) 
{ 
throw new Exception("Testing exception handling") 
} 
}

 spark.stop() }}


On Monday, 6 April 2020 Som Lima <somplasticllc@gmail.com> wrote:
Ok Try this one instead. (link below) 
It has both  an EXIT which we know is  rude and abusive  instead of graceful structured
programming and also includes half hearted  user input validation.
Do you think millions of spark users download and test these programmes and repeat this rude
programming behaviour.
I don't think they have any coding rules like the safety critical software industry But they
do have strict emailing rules.
Do you think email rules are far more important than programming rules and guidelines  ?

https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewStream.scala



On Mon, 6 Apr 2020, 07:04 jane thorpe, <janethorpe1@aol.com.invalid> wrote:

Hi Som ,
Did you know that simple demo program of reading characters from file didn't work ?
Who wrote that simple hello world type little program ?
 
jane thorpe
janethorpe1@aol.com
 
 
-----Original Message-----
From: jane thorpe <janethorpe1@aol.com>
To: somplasticllc <somplasticllc@gmail.com>; user <user@spark.apache.org>
Sent: Fri, 3 Apr 2020 2:44
Subject: Re: HDFS file hdfs://127.0.0.1:9000/hdfs/spark/examples/README.txt

 
Thanks darling
I tried this and worked 

hdfs getconf -confKey fs.defaultFS
hdfs://localhost:9000


scala> :paste
// Entering paste mode (ctrl-D to finish)

val textFile = sc.textFile("hdfs://127.0.0.1:9000/hdfs/spark/examples/README.txt")
val counts = textFile.flatMap(line => line.split(" "))
                 .map(word => (word, 1))
                 .reduceByKey(_ + _)
counts.saveAsTextFile("hdfs://127.0.0.1:9000/hdfs/spark/examples/README7.out")

// Exiting paste mode, now interpreting.

textFile: org.apache.spark.rdd.RDD[String] = hdfs://127.0.0.1:9000/hdfs/spark/examples/README.txt
MapPartitionsRDD[91] at textFile at <pastie>:27
counts: org.apache.spark.rdd.RDD[(String, Int)] = ShuffledRDD[94] at reduceByKey at <pastie>:30

scala> :quit

 
jane thorpe
janethorpe1@aol.com
 
 
-----Original Message-----
From: Som Lima <somplasticllc@gmail.com>
CC: user <user@spark.apache.org>
Sent: Tue, 31 Mar 2020 23:06
Subject: Re: HDFS file

Hi Jane
Try this example 
https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/streaming/HdfsWordCount.scala

Som
On Tue, 31 Mar 2020, 21:34 jane thorpe, <janethorpe1@aol.com.invalid> wrote:

 hi,
Are there setup instructions on the website for spark-3.0.0-preview2-bin-hadoop2.7I can run
same program for hdfs format
val textFile = sc.textFile("hdfs://...")
val counts = textFile.flatMap(line => line.split(" "))
                 .map(word => (word, 1))
                 .reduceByKey(_ + _)
counts.saveAsTextFile("hdfs://...")

val textFile = sc.textFile("/data/README.md")val counts = textFile.flatMap(line => line.split(" "))                 .map(word => (word, 1))                 .reduceByKey(_ + _)counts.saveAsTextFile("/data/wordcount")
textFile: org.apache.spark.rdd.RDD[String] = /data/README.md MapPartitionsRDD[23] at textFile
at <console>:28counts: org.apache.spark.rdd.RDD[(String, Int)] = ShuffledRDD[26] at
reduceByKey at <console>:31


br
Jane 



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