What Is RDD In Spark? | Edureka
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*** Apache Spark and Scala Certification Training: https://www.edureka.co/apache-spark-scala-training *** This Edureka PPT on "RDD Using Spark" will provide you the detailed and comprehensive knowledge about RDD, which are considered to be the backbone of Apache Spark. You will learn about the various Transformations and Actions that can be performed on RDDs. This PPT will cover the following topics: Need for RDDs What are RDDs? Features of RDDs Creation of RDDs using Spark Operations performed on RDDs RDDs using Spark: Pokemon Use Case Blog Series: http://bit.ly/2VRogGx Complete Apache Spark and Scala playlist: http://bit.ly/2In8IXD Follow us to never miss an update in the future. YouTube: https://www.youtube.com/user/edurekaIN Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
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2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
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8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
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- 3. Need for RDDs What are RDDs? Features of RDDs Creation of RDDs using Spark RDDs using Spark Use case Operations performed on RDDs using Spark www.edureka.co
- 8. www.edureka.co • Traditional MapReduce techniques were not suitable for Distributed Iterative Computation • They failed to perform with agility • They created redundancy in data by data replication and data serialization
- 9. www.edureka.co Data Redundancy Data Redundancy Data Latency Data Unavailable Data Available
- 11. WHAT ARE RDDs ? www.edureka.co RDD Fundamental Data Structure of Spark In-Memory Computation Fault Tolerant RDD Multiple Executable nodes Automatic Data Rollback
- 13. www.edureka.co
- 14. www.edureka.co • In-Memory Computation • Lazy Evaluation • Fault Tolerance • Immutability • Partitioning • Persistence • Coarse Grained Operation In-Memory Computation Lazy Evaluations Fault Tolerance Immutability Partitioning Persistence Coarse Grained Operations
- 15. www.edureka.co
- 16. www.edureka.co
- 17. www.edureka.co
- 19. www.edureka.co Transformations are applied on RDDs to Access, Modify and Filter the current RDD to generate a new RDD. The new RDD returns a pointer to the previous RDD to ensure the dependency between them There are two types of Transformations. Namely, • Narrow Transformations • Wide Transformations
- 20. www.edureka.co Narrow Transformations are applied on to a single partition of the parent RDD to generate the new RDD as the data required to process the RDD is available on the single partition of the Parent RDD. Examples: • map() • filter() • flatMap() • partition() • mapPartitions()
- 21. www.edureka.co Wide Transformations are applied on to multiple partitions of an RDD as the data required to generate a new RDD is present among the multiple partitions of the Parent RDD. Examples: • reduceBy() • Union()
- 22. www.edureka.co Actions: Actions are called as the instructions given to Apache Spark to apply the computations and generate the results and display them to the end user.
- 23. www.edureka.co Examples for Actions are: • collect() • count() • take() • First()
- 24. www.edureka.co
- 25. RDDs Using Spark Pokemon Use Case www.edureka.co
- 26. www.edureka.co 1. Load the PokemonData.csv file into an RDD. 2. Remove the schema from the PokemonData.csv file. 3. Find the number of partitions of the PokemonData.csv is split. 4. Find the number of Water and Fire Pokémon. 5. Find the population of Fire, Water and few other types of Pokemon. 6. Filter out the defence column from PokemonData.csv 7. Find the maximum defence strength. 8. Find the Pokemon with maximum Defence. 9. Find the least Defence strength. 10. Find the Pokemon with minimum Defence. Steps to be performed in Pokemon Use Case
- 27. www.edureka.co