Projecting Data¶

Let us understand different aspects of projecting data. We primarily using SELECT to project the data.

We can project all columns using * or some columns using column names.
We can provide aliases to a column or expression using AS in SELECT clause.
DISTINCT can be used to get the distinct records from selected columns. We can also use DISTINCT * to get unique records using all the columns.
As of now Spark SQL does not support projecting all but one or few columns. It is supported in Hive. Following will work in hive and it will project all the columns from orders except for order_id.

SET hive.support.quoted.identifiers=none;
SELECT `(order_id)?+.+` FROM orders;

Let us start spark context for this Notebook so that we can execute the code provided. You can sign up for our 10 node state of the art cluster/labs to learn Spark SQL using our unique integrated LMS.

val username = System.getProperty("user.name")

import org.apache.spark.sql.SparkSession

val username = System.getProperty("user.name")
val spark = SparkSession.
    builder.
    config("spark.ui.port", "0").
    config("spark.sql.warehouse.dir", s"/user/${username}/warehouse").
    enableHiveSupport.
    appName(s"${username} | Spark SQL - Basic Transformations").
    master("yarn").
    getOrCreate

If you are going to use CLIs, you can use Spark SQL using one of the 3 approaches.

Using Spark SQL

spark2-sql \
    --master yarn \
    --conf spark.ui.port=0 \
    --conf spark.sql.warehouse.dir=/user/${USER}/warehouse

Using Scala

spark2-shell \
    --master yarn \
    --conf spark.ui.port=0 \
    --conf spark.sql.warehouse.dir=/user/${USER}/warehouse

Using Pyspark

pyspark2 \
    --master yarn \
    --conf spark.ui.port=0 \
    --conf spark.sql.warehouse.dir=/user/${USER}/warehouse

%%sql

SELECT * FROM orders LIMIT 10

%%sql

DESCRIBE orders

%%sql

SELECT order_customer_id, order_date, order_status FROM orders LIMIT 10

%%sql

SELECT order_customer_id, date_format(order_date, 'yyyy-MM'), order_status FROM orders LIMIT 10

%%sql

SELECT order_customer_id, 
    date_format(order_date, 'yyyy-MM') AS order_month, 
    order_status 
FROM orders LIMIT 10

%%sql

SELECT DISTINCT order_status FROM orders

%%sql

SELECT DISTINCT * FROM orders LIMIT 10

Using Spark SQL with Python or Scala

spark.sql("SELECT * FROM orders").show()

spark.sql("DESCRIBE orders").show()

spark.sql("SELECT order_customer_id, order_date, order_status FROM orders").show()

spark.sql("""
SELECT order_customer_id, 
    date_format(order_date, 'yyyy-MM'), 
    order_status 
FROM orders""").show()

spark.sql("""
SELECT order_customer_id, 
    date_format(order_date, 'yyyy-MM') AS order_month, 
    order_status 
FROM orders
""").show()

spark.sql("SELECT DISTINCT order_status FROM orders").show()

spark.sql("SELECT DISTINCT * FROM orders").show()

Apache Spark using SQL

Projecting Data¶