Spark-shell/pyspark'ta bir RDD parçacığı nasıl yazdırılır?

Question

Kıvılcım kabuğunda çalışırken, sıklıkla RDD'leri incelemek istiyorum (unix'te head kullanımına benzer). Bu (here) nasıl öğrendim ve bu diğer kullanıcılar için faydalı, işte paylaşımı olacak düşünce

scala> val linesContainingSpark = readmeFile.filter(line => line.contains("Spark")) 
scala> // how to inspect linesContainingSpark? 

Answer 1

scala> val readmeFile = sc.textFile("input/tmp/README.md") 
scala> // how to inspect the readmeFile? 

ve ...: Örneğin

. take(x) x öğeleri ve foreach baskılar onları ilk seçer:

scala> val readmeFile = sc.textFile("input/tmp/README.md") 
scala> readmeFile.take(5).foreach(println) 
# Apache Spark 

Spark is a fast and general cluster computing system for Big Data. It provides 
high-level APIs in Scala, Java, and Python, and an optimized engine that 
supports general computation graphs for data analysis. It also supports a 

ve ...

scala> val linesContainingSpark = readmeFile.filter(line => line.contains("Spark")) 
scala> linesContainingSpark.take(5).foreach(println) 
# Apache Spark 
Spark is a fast and general cluster computing system for Big Data. It provides 
rich set of higher-level tools including Spark SQL for SQL and structured 
and Spark Streaming. 
You can find the latest Spark documentation, including a programming 

---

Aşağıdaki örnekler eşdeğer fakat kullanarak pyspark şunlardır:

>>> readmeFile = sc.textFile("input/tmp/README.md") 
>>> for line in readmeFile.take(5): print line 
... 
# Apache Spark 

Spark is a fast and general cluster computing system for Big Data. It provides 
high-level APIs in Scala, Java, and Python, and an optimized engine that 
supports general computation graphs for data analysis. It also supports a 

ve

>>> linesContainingSpark = readmeFile.filter(lambda line: "Spark" in line) 
>>> for line in linesContainingSpark.take(5): print line 
... 
# Apache Spark 
Spark is a fast and general cluster computing system for Big Data. It provides 
rich set of higher-level tools including Spark SQL for SQL and structured 
and Spark Streaming. 
You can find the latest Spark documentation, including a programming