spark vs pyspark

1. Code Writingif (args.length! = 3) {println ("Usage is org.test.WordCount Return}Val sc = new Sparkcontext (args (0), "WordCount",System.getenv ("Spark_home"), Seq (System.getenv ("Spark_test_jar")))Val textfile = Sc.textfile (args (1))Val result = Textfile.flatmap (line = Line.split ("\\s+")). Map (Word (Word, 1)). Reducebykey (_ + _)Result.saveastextfile (args (2))2. Export jar package, here I named Wordcount.jar3. OperationBin/spark-submit--maste

:31)At Com.esotericsoftware.kryo.Kryo.readObject (kryo.java:711)At Com.esotericsoftware.kryo.serializers.ObjectField.read (objectfield.java:125)... More16/05/24 09:42:53 ERROR sparksqldriver:failed in [selectDt.d_year, item.i_brand_id brand_id, Item.i_brand Brand, SUM (ss_ext_sales_price) Sum_aggFrom Date_dim DT, Store_sales, itemwhere Dt.d_date_sk = Store_sales.ss_sold_date_skand Store_sales.ss_item_sk = Item.i_item_skand item.i_manufact_id = 436and dt.d_moy=12GROUP BY Dt.d_year, Item.i_brand,

When a task executes a commit failure, it retries, and the default retry count for the task is 4 times. def this (sc:sparkcontext) = This (SC, sc.conf.getInt ("Spark.task.maxFailures", 4)) (Taskschedulerimpl)(2) Add TasksetmanagerSchedulerbuilder (depending on the Schedulermode, FIFO is different from fair implementation) #addTaskSetManger方法会确定TaskSetManager的调度顺序, Then follow Tasksetmanager's locality aware to determine that each task runs specifically in that executorbackend. The default schedu

This lesson: The use of Scala's implicit in the Spark source code Scala's implicit programming operation combat Scala's implicit enterprise-class best practices The use of Scala's implicit in the Spark source codeThe meaning of this thing is very significant, the RDD itself does not have a key, value, but it is the time of its own interpretation into a key Value of the method to read,

You are welcome to reprint it. Please indicate the source, huichiro.Summary There is nothing to say about source code compilation. For Java projects, as long as Maven or ant simple commands are clicked, they will be OK. However, when it comes to spark, it seems that things are not so simple. According to the spark officical document, there will always be compilation errors in one way or another, which is an

stay at home for 10 hours, stay in the company for 8 hours, and may be passing by some base station in the car. Ideas: For each cell phone number under which base station to stay the longest time, in the calculation, with "mobile phone number + base station" in order to locate under which base station stay at the time, Because there will be a lot of user log data under each base station. The country has a lot of base stations, each telecommunications branch is only responsible for calcula

HDFs, which is only created once to be used permanently, as follows: createfunction Func.iptolocationbysina as ' Com.sina.dip.hive.function.IPToLocationBySina ' usingjar ' hdfs:// Dip.cdh5.dev:8020/user/hdfs/func/location.jar '; Although the permanent function has some advantages over the temporal function, the development threshold of the Java language largely hinders the use of UDFs in the actual data analysis process. After all, our data analysts are mostly Python, SQL as the main analysis t

1. Download Spark and run wget http://apache.fayea.com/apache-mirror/spark/spark-1.0.0/spark-1.0.0-bin-hadoop2.tgz I'm the download here is version 1.0.0, because we just test the use of spark, so do not need to configure the spark