CCA 175 Exam preparation using Scala & Practice Tests [2020]

Explore map and flatMap transformations in scala by applying functions to each element, calculating line lengths, and using flatMap to split lines into multiple output elements.

Learn how distinct transformation removes duplicates from an rdd, and how union transformation merges two rdds into one, with examples using in-memory data structures and concepts like map and flatMap.

Explore how reduceByKey aggregates total students per subject by shuffling data across a cluster, using an accumulator and x plus y to sum science, maths, and computer enrollments.

Master string manipulation with the data frame API: uppercase first names, lowercase last names, concatenate with a delimiter, replace patterns with regex, and split emails into parts.

explains how to access Hive tables from Spark, create a DataFrame, run Spark SQL on Hive, and write results back to Hive as a new table.

Explore hive/spark sql mathematical functions, including round, floor, rand, log, sqrt, power, factorial, sine, cosine, radians to degrees, and bit-shift operations, with practical demonstrations.

Explore Hive/Spark SQL analytics functions to group by city, count customers, and apply having and if logic, with MapReduce behind the scenes.

Explore how to compute the maximum product price per product category using Spark SQL: group by category, max(price), and save as text with GSM compression ordered by maximum price descending.

Read a tab-delimited customer file and filter Lagos state residents using Spark. Define the output schema with customer_id, customer_name, and customer_city; cast id to integer and save with deflate compression.

Execute a spark-based transformation to extract the first three letters of the first name and save a tab-delimited, compressed file with customer ID, the first-name letters, and the last name.