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Spark interview Q&As with coding examples in Scala – part 02: partition pruning & column projection

This extends Spark interview Q&As with coding examples in Scala – part 1 with the key optimisation concepts.

Partition Pruning

Q13. What do you understand by the concept Partition Pruning?
A13. Spark & Hive table partitioning by year,

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Spark interview Q&As with coding examples in Scala – part 03: Partitioning, pruning & predicate push down

This extends Spark interview Q&As with coding examples in Scala – part 2 with more coding examples on Databricks Note book. Prerequisite: Create a free account as per Databricks getting started. Login to community.cloud.databricks.com, and click on “ … Read more ›...

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Spark interview Q&As with coding examples in Scala – part 04: Memory considerations, lazy computation & cacheing

This extends Spark interview Q&As with coding examples in Scala – part 3 with more coding examples on Databricks Note book. Prerequisite: Create a free account as per Databricks getting started. Login to community.cloud.databricks.com, and click on “ … Read more ›...

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Spark interview Q&As with coding examples in Scala – part 05: Transformations, actions, pipelining & shuffling

This extends Spark interview Q&As with coding examples in Scala – part 4 with more coding examples on Databricks Note book.

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Spark interview Q&As with coding examples in Scala – part 06: groupBy, collect_list & explode

This extends Spark interview Q&As with coding examples in Scala – part 5 with more coding examples on Databricks Note book. Prerequisite: Create a free account as per Databricks getting started. Login to community.cloud.databricks.com, and click on “ … Read more ›...

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Spark interview Q&As with coding examples in Scala – part 07: map, flatMap, mapPartitions & mapValues

This extends Spark interview Q&As with coding examples in Scala – part 6 with more coding examples on Databricks Note book. Prerequisite: Create a free account as per Databricks getting started. Login to community.cloud.databricks.com, and click on “ … Read more ›...

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Spark interview Q&As with coding examples in Scala – part 08: pivot, unpivot, agg & selectExpr

This extends Spark interview Q&As with coding examples in Scala – part 7 with more coding examples on Databricks Note book. Prerequisite: Create a free account as per Databricks getting started. Login to community.cloud.databricks.com, and click on “ … Read more ›...

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Spark interview Q&As with coding examples in Scala – part 09: sql.functions

This extends Spark interview Q&As with coding examples in Scala – part 8 with more coding examples on Databricks Note book. Prerequisite: Create a free account as per Databricks getting started. Login to community.cloud.databricks.com, and click on “ … Read more ›...

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Spark interview Q&As with coding examples in Scala – part 10: adding new columns

This covers one of the most popular Spark interview questions of adding new columns to Spark Dataframes. Most non-trivial Spark jobs will have additional columns added to an existing Dataframe. These columns can be derived from existing columns in a Dataframe.

Q01. What are the different ways in which you can add new columns to a Dataframe?

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Spark interview Q&As with coding examples in Scala – part 11: add column values conditionally, lit & typedlit

This extends Spark interview Q&As with coding examples in Scala – part 10: adding new columns. Q01. How will you add a new column with a fixed value? A01. Using the lit(..) & typedlit(..) functions in “org.apache.spark.sql.functions” … Read more ›...

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Spark join strategies & performance tuning interview questions and answers

Join operations are frequently used in big data analytics to merge two data sets, represented as tables, DataSets or DataFrames via on a matching key. Being aware of these join strategies is important as they can significantly impact the performance and efficiency of your Spark applications. Q1. … Read more...

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Spark understanding DAG for tuning performance interview questions and answers

This extends 15 Apache Spark best practices & performance tuning interview FAQs to delve into DAGs, Stages, Tasks, Partitions and Shuffling in Spark. If you can’t read Spark Event Timelines & DAGs, you will be running blind as to how efficient your code is. … Read more ›...

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SQL procedures vs functions with postgresql (i.e. plpgsql) examples

Q01 What is the difference between SQL stored Procedures & Functions?
A01 Stored procedure does not have a RETURNS clause, but you can use the OUT or INOUT parameter. Stored procedures are transactional whereas functions are not.

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