README.md

rSHARK

rSHARK provides an R library for creating Apache Spark dataframes with SmartSHARK data. The data can then be analyzed with SparkR.

Prerequistes

Two prerequisites are required:

  1. A working installation of SparkR. The guide for the installation, including how to load SparkR with RStudio can be found here.
  2. The sparkSHARK.jar file, which can be downloaded here.

Installation

Once SparkR is running, rSHARK can be installed directly from this repository using the devtools:

if (!require("devtools")) install.packages("devtools")
library(devtools)
install_github("smartshark/rSHARK")

Usage

You first need to load SparkR and rSHARK:

library(SparkR)
library(rSHARK)

Then, you must create a Spark session:

sparkSession <- sparkR.session(master=SPARK_MASTER,
                               sparkConfig=list(spark.driver.extraClassPath="SPARKSHARK_JAR",
                                                spark.driver.extraLibraryPath="SPARKSHARK_JAR",
                                                spark.driver.extraJavaOptions=JAVA_OPTIONS),
                               sparkJars=SPARKSHARK_JAR)

You have to replace SPARK_MASTER, SPARKSHARK_JAR, and JAVA_OPTIONS with the correct values: - SPARK_MASTER: the address of the Spark master (see here) - SPARKSHARK_JAR: location of the sparkSHARK.jar file. - JAVA_OPTIONS: arguments to to the JVM used for the Spark execution. These arguments should be used to setup the data base connection, as described here.

Using the Spark session, you can initialize the database utilities for accessing the data:

mongoDBUtils <- rShark.createMongoDBUtils(sparkSession)

You can then use the rShark.loadData() and rShark.loadDataLogical() commands for accessing the data.

Examples

Please find some helpful code snippets below. Complete rSHARK Jobs can be found here.

Example 1: Initialize a local Spark and a local MongoDB

SPARK_MASTER <- local[*]
SPARKSHARK_JAR <- "/users/jsmith/jars/sparkSHARK.jar"
JAVA_OPTIONS <- paste("-Dspark.exectutorEnv.dbtuils.type=mongo",
                      "-Dspark.executorEnv.mongo.uri=localhost",
                      "-Dspark.executorEnv.mongo.port=27017",
                      "-Dspark.executorEnv.mongo.dbname=smartshark")

sparkSession <- sparkR.session(master=SPARK_MASTER,
                               sparkConfig=list(spark.driver.extraClassPath=SPARKSHARK_JAR,
                                                spark.driver.extraLibraryPath="SPARKSHARK_JAR",
                                                spark.driver.extraJavaOptions=JAVA_OPTIONS),
                               sparkJars=SPARKSHARK_JAR)
mongoDBUtils <- rShark.createMongoDBUtils(sparkSession)

Example 2: Initialize a remote Spark session and a MongoDB with authentication

SPARK_MASTER <- spark://YOURHOST:YOURPORT
SPARKSHARK_JAR <- "/users/jsmith/jars/sparkSHARK.jar"
JAVA_OPTIONS <- paste("-Dspark.exectutorEnv.dbtuils.type=mongo",
                      "-Dspark.executorEnv.mongo.uri=http://somehost/",
                      "-Dspark.executorEnv.mongo.port=27017",
                      "-Dspark.executorEnv.mongo.dbname=smartshark",
                      "-Dspark.executorEnv.mongo.useauth=true",
                      "-Dspark.executorEnv.mongo.username=USER",
                      "-Dspark.executorEnv.mongo.authdb=admin",
                      "-Dspark.executorEnv.mongo.password=PASSWORD")

sparkSession <- sparkR.session(master=SPARK_MASTER,
                               sparkConfig=list(spark.driver.extraClassPath=SPARKSHARK_JAR,
                                                spark.driver.extraLibraryPath="SPARKSHARK_JAR",
                                                spark.driver.extraJavaOptions=JAVA_OPTIONS),
                               sparkJars=SPARKSHARK_JAR)
mongoDBUtils <- rShark.createMongoDBUtils(sparkSession)

Example 3: Loading data

# Load all data from the commit collection
rShark.loadData(mongoDBUtils, "commit")

# Loads the document ID and the product metrics available for Java classes
# from the entity_state collection
rShark.loadDataLogical(mongoDBUtils,
                       "code_entity_state",
                       list(c("AbstractionLevel"), c("ProductMetric", "JavaClass")))


smartshark/rSHARK documentation built on May 26, 2017, 12:25 p.m.