Data Engineering Spark SQL - Windowing Functions - Using LEAD or LAG

Databases Postgres
1

Let us understand LEAD and LAG functions to get column values from following or prior records.
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 spark = SparkSession.
    builder.
    config("spark.ui.port", "0").
    config("spark.sql.warehouse.dir", s"/user/${username}/warehouse").
    enableHiveSupport.
    appName(s"${username} | Spark SQL - Windowing Functions").
    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

Here is the example where we can get prior or following records based on ORDER BY within OVER Clause.

USE itversity_retail

SELECT * FROM daily_revenue
ORDER BY order_date DESC
LIMIT 10

SELECT t.*,
  lead(order_date) OVER (ORDER BY order_date DESC) AS prior_date,
  lead(revenue) OVER (ORDER BY order_date DESC) AS prior_revenue,
  lag(order_date) OVER (ORDER BY order_date) AS lag_prior_date,
  lag(revenue) OVER (ORDER BY order_date) AS lag_prior_revenue
FROM daily_revenue AS t
ORDER BY order_date DESC
LIMIT 10

SELECT t.*,
  lead(order_date) OVER (ORDER BY order_date DESC) AS prior_date,
  lead(revenue) OVER (ORDER BY order_date DESC) AS prior_revenue
FROM daily_revenue AS t
ORDER BY order_date
LIMIT 10

We can also pass the number of rows as well as default values for nulls as arguments.

USE itversity_retail

SELECT t.*,
  lead(order_date, 7) OVER (ORDER BY order_date DESC) AS prior_date,
  lead(revenue, 7) OVER (ORDER BY order_date DESC) AS prior_revenue
FROM daily_revenue t
ORDER BY order_date DESC
LIMIT 10

SELECT t.*,
  lead(order_date, 7) OVER (ORDER BY order_date DESC) AS prior_date,
  lead(revenue, 7) OVER (ORDER BY order_date DESC) AS prior_revenue
FROM daily_revenue t
ORDER BY order_date
LIMIT 10

SELECT t.*,
  lead(order_date, 7, 'NA') OVER (ORDER BY order_date DESC) AS prior_date,
  lead(revenue, 7, 0) OVER (ORDER BY order_date DESC) AS prior_revenue
FROM daily_revenue t
ORDER BY order_date
LIMIT 10

Let us see how we can get prior or following records within a group based on a particular order.

Here is the example where we can get prior or following records based on PARTITION BY and then ORDER BY Clause.

USE itversity_retail

DESCRIBE daily_product_revenue

SELECT * FROM daily_product_revenue 
ORDER BY order_date, revenue DESC
LIMIT 10

SELECT t.*,
  LEAD(order_item_product_id) OVER (
    PARTITION BY order_date 
    ORDER BY revenue DESC
  ) next_product_id,
  LEAD(revenue) OVER (
    PARTITION BY order_date 
    ORDER BY revenue DESC
  ) next_revenue
FROM daily_product_revenue t
ORDER BY order_date, revenue DESC
LIMIT 100

We can also pass the number of rows as well as default values for nulls as arguments.

SELECT t.*,
  LEAD(order_item_product_id) OVER (
    PARTITION BY order_date ORDER BY revenue DESC
  ) next_product_id,
  LEAD(revenue, 1, 0) OVER (
   

[Watch the video tutorial here](https://www.youtube.com/watch?v=pFOauTRc_-E)