Created
November 13, 2015 18:42
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Dir["./spark/lib/*.jar"].each { |jar| require jar } | |
require "~/sqljdbc/sqljdbc42.jar" | |
import java.util.HashMap | |
import org.apache.spark.SparkConf | |
import org.apache.spark.api.java.JavaSparkContext | |
import org.apache.spark.sql.SQLContext | |
AWS_KEY = ENV["AWS_KEY"] | |
AWS_SECRET = ENV["AWS_SECRET"] | |
S3_BUCKET = "tomzeng/rdd_output" | |
SQL_DRIVER = "com.microsoft.sqlserver.jdbc.SQLServerDriver" | |
SQL_USERNAME = ENV["SQL_USERNAME"] | |
SQL_PWD = ENV["SQL_PWD"] | |
SQL_HOST_PORT = "ngc1379w4v.database.windows.net:1433" | |
SQL_DB = "sample" | |
SQL_CONNECTION_URL = "jdbc:sqlserver://#{SQL_HOST_PORT};database=#{SQL_DB};user=#{SQL_USERNAME};password=#{SQL_PWD};encrypt=true;trustServerCertificate=false;hostNameInCertificate=*.database.windows.net;loginTimeout=30;" | |
sc = JavaSparkContext.new(SparkConf.new.set_app_name("JRuby Spark JDBC DF S3").set_master("local[*]")) | |
sql_context = SQLContext.new(sc) | |
options = {"driver" => SQL_DRIVER, "url" => SQL_CONNECTION_URL, "dbtable" => "SalesLT.Customer"} | |
# load the table into data frame | |
jdbc_df = sql_context.load("jdbc", options) | |
# display the table rows | |
customer_rows = jdbc_df.collect_as_list() | |
customer_rows.each {|row| puts row} | |
# saving the SQL Server table to s3 | |
jdbc_df.select("*").write().format("com.databricks.spark.csv").save("s3n://#{AWS_KEY}:#{AWS_SECRET}@#{S3_BUCKET}") |
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