I am trying to use a WEB URL from spark-shell using textFile method, but getting error. Probably this is not the right way. So can someone please tell me how to access a web URL from spark context.
I am using spark version 1.3.0 ; Scala version 2.10.4 and Java 1.7.0_21
hduser@ubuntu:~$ spark-shell
Spark assembly has been built with Hive, including Datanucleus jars on classpath
Welcome to
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/ / / /
\ \/ \/ `/ _/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 1.3.0
/_/
Using Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.7.0_21)
Type in expressions to have them evaluated.
Type :help for more information.
Spark context available as sc.
SQL context available as sqlContext.
scala> val pagecount = sc.textFile( "https://www.google.co.in/?gws_rd=ssl" )
pagecount: org.apache.spark.rdd.RDD[String] = https://www.google.co.in/?gws_rd=ssl MapPartitionsRDD[1] at textFile at <console>:21
scala> pagecount.count()
java.io.IOException: No FileSystem for scheme: https
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:1383)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:66)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:1404)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:254)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:187)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:176)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:208)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:203)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1511)
at org.apache.spark.rdd.RDD.count(RDD.scala:1006)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:24)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:29)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:31)
at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:33)
at $iwC$$iwC$$iwC$$iwC.<init>(<console>:35)
at $iwC$$iwC$$iwC.<init>(<console>:37)
at $iwC$$iwC.<init>(<console>:39)
at $iwC.<init>(<console>:41)
at <init>(<console>:43)
at .<init>(<console>:47)
at .<clinit>(<console>)
at .<init>(<console>:7)
at .<clinit>(<console>)
at $print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:601)
at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1338)
at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:856)
at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:901)
at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:813)
at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:656)
at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:664)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:669)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:996)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:944)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:944)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:944)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1058)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:601)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
If you are running the Spark application locally, Spark UI can be accessed using the http://localhost:4040/ . Spark UI by default runs on port 4040 and below are some of the additional UI's that would be helpful to track Spark application. Note: To access these URLs, Spark application should in running state.
To create a SparkContext you first need to build a SparkConf object that contains information about your application. The appName parameter is a name for your application to show on the cluster UI. master is a Spark, Mesos or YARN cluster URL, or a special “local” string to run in local mode.
A SparkContext represents the connection to a Spark cluster, and can be used to create RDDs, accumulators and broadcast variables on that cluster. Only one SparkContext should be active per JVM. You must stop() the active SparkContext before creating a new one.
You cannot get url content using textFile
directly. textFile
is to :
Read a text file from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI
You see, HTTP/HTTPS
url is not included.
You can get the content first, and then make it as RDDs
.
val html = scala.io.Source.fromURL("https://spark.apache.org/").mkString
val list = html.split("\n").filter(_ != "")
val rdds = sc.parallelize(list)
val count = rdds.filter(_.contains("Spark")).count()
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