Differences
This shows you the differences between two versions of the page.
Next revision | Previous revision Next revision Both sides next revision | ||
spark:spark-introduction [2014/10/03 10:22] straka created |
spark:spark-introduction [2014/10/06 11:25] straka |
||
---|---|---|---|
Line 1: | Line 1: | ||
====== Spark Introduction ====== | ====== Spark Introduction ====== | ||
- | ===== Spark Introduction | + | This introduction shows several simple examples to give you an idea what programming |
- | ===== Spark Introduction | + | ===== Running |
+ | |||
+ | To run interactive Python shell in local Spark mode, run (on your local workstation or on cluster) | ||
+ | <file bash> | ||
+ | IPYTHON=1 pyspark | ||
+ | </ | ||
+ | The IPYTHON=1 parameter instructs Spark to use '' | ||
+ | |||
+ | After a local Spark executor is started, the Python shell starts. | ||
+ | 14/10/03 10:54:35 INFO SparkUI: Started SparkUI at http:// | ||
+ | |||
+ | ==== Running Spark Shell in Scala ==== | ||
+ | |||
+ | To run interactive Scala shell in local Spark mode, run (on your local workstation or on cluster) | ||
+ | <file bash> | ||
+ | spark-shell | ||
+ | </ | ||
+ | Once again, the SparkUI address is listed several lines above the shell prompt line. | ||
+ | |||
+ | |||
+ | ===== Word Count Example ===== | ||
+ | |||
+ | The central object of Spark framework is RDD -- resilient distributed dataset. It contains ordered sequence of items, which may be distributed in several threads or on several computers. Spark offers multiple operations which can be performed on RDD, like '' | ||
+ | |||
+ | 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: | ||
+ | <file python> | ||
+ | wiki = sc.textFile("/ | ||
+ | words = wiki.flatMap(lambda line: line.split()) | ||
+ | counts = words.map(lambda word: (word, 1)).reduceByKey(lambda c1,c2: c1+c2) | ||
+ | sorted = counts.sortBy(lambda (word, | ||
+ | sorted.saveAsTextFile(' | ||
+ | |||
+ | # Alternatively, | ||
+ | (sc.textFile("/ | ||
+ | | ||
+ | | ||
+ | | ||
+ | | ||
+ | | ||
+ | </ | ||
+ | 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("/ | ||
+ | | ||
+ | | ||
+ | | ||
+ | | ||
+ | </ | ||