spark mllib example

Operating system: Windows 10Idea:idea 14.1.41: Use idea to import the Spark 1.5 source, note that MAVEN is configured to import automatically2: Check the options for Hadoop, Hive, Hive-thriftserver,yarn in the profiles under the Maven window.3: Check the genertate sourec command under the Maven window4: Change all dependency of the module example to compileReplace Pom.xml First, then the missing one which m

[Spark] [Python] [DataFrame] [Rdd] Example of getting an RDD from Dataframe$ HDFs Dfs-cat People.json{"Name": "Alice", "Pcode": "94304"}{"Name": "Brayden", "age": +, "Pcode": "94304"}{"Name": "Carla", "age": +, "Pcoe": "10036"}{"Name": "Diana", "Age": 46}{"Name": "Etienne", "Pcode": "94104"}$pysparkSqlContext = Hivecontext (SC)PEOPLEDF = SqlContext.read.json ("People.json")Peoplerdd = Peopledf.rddPeoplerdd.

1. Operator Classification From the general direction, the Spark operator can be broadly divided into the following two types of transformation: The operation is deferred calculation, that is, the conversion from one RDD to another rdd is not executed immediately, it is necessary to wait until there is an action action to actually trigger the operation. Action: Triggers the Spark submission job (job) and o

[Spark] [Python] [RDD] [DataFrame] from the RDD construction DataFrame ExampleFrom pyspark.sql.types Import *schema = Structtype ([Structfield ("Age", Integertype (), True),Structfield ("Name", StringType (), True),Structfield ("Pcode", StringType (), True)])Myrdd = Sc.parallelize ([(+, "Abram", "01601"), (+, "Lucia", "87501")])MYDF = Sqlcontext.createdataframe (Myrdd,schema)Mydf.limit (5). Show ()+---+-----+-----+|age| name|pcode|+---+-----+-----+| 4

Org.apache.spark.api.java.function.function#call (java.lang.Object)*/ PublicQualify Call (String v1)throwsException {//TODO auto-generated Method StubString s[] = V1.split (","); Qualify Q=NewQualify (); Q.seta (Integer.parseint (s[0])); Q.setb (Long.parselong (s[1])); Q.SETC (s[2]); returnQ; } }); Map.persist (Storagelevel.memory_and_disk_ser ()); System.out.println (Map.count ()); }}ImportOrg.apache.spark.serializer.KryoRegistrator;ImportCom.esotericsoftwar

Operating EnvironmentCluster Environment: CDH5.3.0The specific jar versions are as follows:Spark version: 1.2.0-cdh5.3.0Hive Version: 0.13.1-cdh5.3.0Hadoop version: 2.5.0-cdh5.3.0Simple Java version of Spark SQL sample Spark SQL directly queries JSON-formatted data Custom functions for Spark SQL Spark

type, which is slightly different from Updatestatebykey. Here is an example /** Mapwithstate.function is the state pair (K,V) of each key to map * Each of the input (Stockmame,stockprice) key value pairs, using the state of each key to map, Returns the new results * Here the state is the last price of each stockname * with the input (Stockname,stockprice) StockPrice the last price in the state ( state.update function) * Mapping res

[Continuation of the Spark][python]sortbykey example:[Spark] [Python]groupbykey ExampleIn []: Mydata003.collect ()OUT[29]:[[u ' 00001 ', U ' sku933 '],[u ' 00001 ', U ' sku022 '],[u ' 00001 ', U ' sku912 '],[u ' 00001 ', U ' sku331 '],[u ' 00002 ', U ' sku010 '],[u ' 00003 ', U ' sku888 '],[u ' 00004 ', U ' sku411 ']in [+]: Mydata005=mydata003.groupbykey ()in [+]

Spark Streaming Application Simple example Package Com.orc.stream Import org.apache.spark.{ sparkconf, Sparkcontext} import org.apache.spark.streaming.{ Seconds, StreamingContext} /** * Created by Dengni on 2016/9/15. Today also are mid-Autumn Festival * Scala 2.10.4 ; 2.11.X not Works * Use method: * Start this program in this window * 192.168.184.188 Start command nc-l 7777 input valu

Start by creating a new Maven project in Eclipse Java EE with the following specific optionsClick Finish to create a success, then change the default jdk1.5 to jdk1.8Then edit Pom.xml Join Spark-core DependencyThen copy the source code sample program in the book, because the spark version in the book is 1.2 My environment spark is 2.2.1 so need to modify the code

[Spark] [Python]sortbykey Example:[Email protected] ~]$ HDFs dfs-cat test02.txt00002 sku01000001 sku93300001 sku02200003 sku88800004 sku41100001 sku91200001 sku331[Email protected] ~]$Mydata001=sc.textfile ("Test02.txt")Mydata002=mydata001.map (Lambda line:line.split ("))Mydata002.take (3)OUT[4]: [[u ' 00002 ', U ' sku010 '], [u ' 00001 ', U ' sku933 '], [u ' 00001 ', U ' sku022 ']Mydata003=mydata002.sortby

Example of the RDD FlatMap operation:FlatMap, performs a function operation on each element (line) of the original Rdd, and then "beats" each line[Email protected] ~]$ HDFs dfs-put cats.txt[Email protected] ~]$ HDFs dfa-cat cats.txtError:could not find or load main class DFA[Email protected] ~]$ HDFs dfs-cat cats.txtThe Cat on the matThe aardvark sat on the sofaMydata=sc.textfile ("Cats.txt")Mydata.count ()OUT[14]: 2Mydata.take (2)OUT[15]: [u ' the Ca

Tags: declaring localhost lis problem eset no ICA normal OSIRecently in the Watch Learning spark Framework. This is a web framework, as its website link shows: SPARK-A Micro framework for creating Web applications in Kotlin and Java 8 with minimal effort I follow its example to learn. Here comes the Blogservice project [portal], which is also an