Posts

Showing posts with the label Spark SQL

Featured Post

Step-by-Step Guide to Creating an AWS RDS Database Instance

-
Image
 Amazon Relational Database Service (AWS RDS) makes it easy to set up, operate, and scale a relational database in the cloud. Instead of managing servers, patching OS, and handling backups manually, AWS RDS takes care of the heavy lifting so you can focus on building applications and data pipelines. In this blog, we’ll walk through how to create an AWS RDS instance , key configuration choices, and best practices you should follow in real-world projects. What is AWS RDS? AWS RDS is a managed database service that supports popular relational engines such as: Amazon Aurora (MySQL / PostgreSQL compatible) MySQL PostgreSQL MariaDB Oracle SQL Server With RDS, AWS manages: Database provisioning Automated backups Software patching High availability (Multi-AZ) Monitoring and scaling Prerequisites Before creating an RDS instance, make sure you have: An active AWS account Proper IAM permissions (RDS, EC2, VPC) A basic understanding of: ...
Post a Comment
Read more

Spark SQL Query how to write it in Ten steps

-
Image
Spark SQL example The post tells how to write SQL query in Spark and explained in ten steps.This example demonstrates how to use sqlContext.sql to create and load two tables and select rows from the tables into two DataFrames. The next steps use the DataFrame API to filter the rows for salaries greater than 150,000 from one of the tables and shows the resulting DataFrame. Then the two DataFrames are joined to create a third DataFrame. Finally the new DataFrame is saved to a Hive table. 1. At the command line, copy the Hue sample_07 and sample_08 CSV files to HDFS: $ hdfs dfs -put HUE_HOME/apps/beeswax/data/sample_07.csv /user/hdfs $ hdfs dfs -put HUE_HOME/apps/beeswax/data/sample_08.csv /user/hdfs where HUE_HOME defaultsto /opt/cloudera/parcels/CDH/lib/hue (parcel installation) or /usr/lib/hue (package installation). 2. Start spark-shell: $ spark-shell 3. Create Hive tables sample_07 and sample_08: scala> sqlContext.sql("CREATE TABLE sample_07 (code string...
Post a Comment
Read more