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spark:spark-introduction [2014/10/03 14:43] straka |
spark:spark-introduction [2014/10/06 11:27] straka |
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To run interactive Python shell in local Spark mode, run (on your local workstation or on cluster) | To run interactive Python shell in local Spark mode, run (on your local workstation or on cluster) | ||
- | | + | <file bash> |
- | The IPYTHON=1 parameter instructs Spark to use '' | + | IPYTHON=1 pyspark |
+ | </ | ||
+ | The IPYTHON=1 parameter instructs Spark to use '' | ||
After a local Spark executor is started, the Python shell starts. | After a local Spark executor is started, the Python shell starts. | ||
Line 15: | Line 17: | ||
To run interactive Scala shell in local Spark mode, run (on your local workstation or on cluster) | To run interactive Scala shell in local Spark mode, run (on your local workstation or on cluster) | ||
- | scala-shell | + | <file bash> |
+ | spark-shell | ||
+ | </ | ||
Once again, the SparkUI address is listed several lines above the shell prompt line. | Once again, the SparkUI address is listed several lines above the shell prompt line. | ||
Line 24: | Line 28: | ||
Here we load the RDD from text file, every line of the input file becoming an element of RDD. We then split every line into words, count every word occurrence and sort the words by the occurrences. Try the following in the opened Python shell: | Here we load the RDD from text file, every line of the input file becoming an element of RDD. We then split every line into words, count every word occurrence and sort the words by the occurrences. Try the following in the opened Python shell: | ||
- | w = sc.textFile('/ | + | <file python> |
- | words = w.flatMap(lambda line: line.split()) | + | wiki = sc.textFile("/ |
- | counts = words.map(lambda word: (word, 1)).reduceByKey(lambda c1,c2: c1+c2) | + | words = wiki.flatMap(lambda line: line.split()) |
- | sorted = counts.sortBy(lambda (word, | + | counts = words.map(lambda word: (word, 1)).reduceByKey(lambda c1,c2: c1+c2) |
- | sorted.saveAsTextFile(' | + | sorted = counts.sortBy(lambda (word, |
- | + | sorted.saveAsTextFile(' | |
- | # Alternatively, | + | |
- | sc.textFile('/ | + | # Alternatively, |
- | .flatMap(lambda line: line.split()) | + | (sc.textFile("/ |
- | .map(lambda word: (word, 1)) \ | + | |
- | .reduceByKey(lambda c1,c2: c1+c2) | + | |
- | .sortBy(lambda (word, | + | |
- | .take(100) # Instead of saveAsTextFile, | + | |
+ | | ||
+ | </ | ||
The output of ' | The output of ' | ||
+ | |||
+ | The Scala versions is quite similar: | ||
+ | <file scala> | ||
+ | val wiki = sc.textFile("/ | ||
+ | val words = wiki.flatMap(line => line.split(" | ||
+ | val counts = words.map(word => (word, | ||
+ | val sorted = counts.sortBy({case (word, count) => count}, ascending=false) | ||
+ | sorted.saveAsTextFile(' | ||
+ | |||
+ | // Alternatively without variables and using placeholders in lambda parameters: | ||
+ | (sc.textFile("/ | ||
+ | | ||
+ | | ||
+ | | ||
+ | | ||
+ | </ | ||
+ |