Apache Spark
11 resources created by 9 users
This Apache Spark page on GoConqr brings together community-made mind maps, notes, flashcards, a quiz and slides, covering RDDs, DataFrames and Spark concepts. It is for university students and professional candidates studying these topics, and teachers looking for ready-made material. The small set of resources includes material at university and professional levels. Pick a resource to start exploring the topic.
Apache Spark
- All Big Data, Hadoop and Spark resources
- Big Data History and Evolution14
- Big Data Concepts and Characteristics44
- Big Data Architecture and Engineering16
- Big Data Storage and NoSQL12
- Big Data Analytics18
- Data Analytics Lifecycle9
- Big Data Applications in Business13
- Cloud Computing for Big Data15
- Hadoop Architecture and Ecosystem57
- Hadoop MapReduce5
- Big Data Processing Tools10
Top Apache Spark resources
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25 questionsData Architecture test What's the right data timing classification to keep in mind when choosing a data ingestion tool?
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29 cardsApache Spark Concepts Apache Spark or MapReduce
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15 nodesRDD-based programming SparkContext · RDD
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37 nodesSpark Transformaciones con RDD · Transformaciones de u... · Acciones mas habitual... · Fuentes de datos · Job · Stage
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11 nodesDataFrame Extends RDD & contain... · can run SQL queries o... · has a schema = leadin... · to create it, we use ... · Transformations = sel... · since Spark 2.0 it's ...
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37 nodesApache Spark Architecture · Deployment Mode · HDFS
Quizzes
Mind maps
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15 nodesRDD-based programming SparkContext · RDD
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37 nodesSpark Transformaciones con RDD · Transformaciones de u... · Acciones mas habitual... · Fuentes de datos · Job · Stage
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11 nodesDataFrame Extends RDD & contain... · can run SQL queries o... · has a schema = leadin... · to create it, we use ... · Transformations = sel... · since Spark 2.0 it's ...
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37 nodesApache Spark Architecture · Deployment Mode · HDFS
Flashcards
Notes
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Spark learning Strongly typed language and week typed:- The difference between a strongly typed language and a weakly typed language is basically that a strongly typed language checks the type of a variable before performi...
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Filter and Map Filter data //create person.txt Name, Age Vinayak, 35 Nilesh, 37 Raju, 30 Karthik, 28 Shreshta,1 Siddhish, 2 val personfile = sc.textFile("C:/Users/Redirection/pateln7/Downloads/SPARK/person.txt") val fi...
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Joins // JOINS ===================================== Using RDD //emp table id,name,age 1,Vinayak, 35 2,Nilesh, 37 3,Raju, 30 4,Karthik, 28 5,Shreshta,1 6,Siddhish, 2 val emp = sc.textFile(...
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Untitled
Slides
More Big Data, Hadoop and Spark topics
About Apache Spark
GoConqr OriginalStart with Spark concepts
The Apache Spark page brings together resources made by GoConqr users. If you want an overview, start with the Apache Spark mind map. It covers architecture, driver and executor processes, Spark sessions, jobs, stages and tasks. It also introduces logical and physical execution plans and directed acyclic graphs.
The Apache Spark Concepts flashcards cover several of these terms too. Use them after the map to check whether you can recall the terms without looking at the overview.
Explore RDDs and DataFrames
The RDD-based programming mind map looks at SparkContext and ways to create an RDD, including loading an external dataset or parallelizing a local collection. The DataFrame map covers row objects, schemas and running SQL queries on a SparkSession object.
For examples in notes, look at Filter and Map and Joins. The slides titled Difference between DataSet API and DataFrame API introduce the RDD, DataFrame and Dataset APIs. These resources offer different ways to study alongside the maps.
Use the quiz with the maps
The Data Architecture test includes questions about data ingestion, Apache Kafka and reusing a DataFrame. After taking it, return to the DataFrame mind map to go over the relevant ideas. You can also use the maps first and take the quiz afterward to check your understanding.
Place the topic in its unit
Apache Spark is a section of Big Data, Hadoop and Spark in the Databases and data science subject. The resources on this page give you a way to focus on Spark concepts within that unit, from architecture terms to RDDs and DataFrames. Choose a map or a set of notes and begin with the area you want to study.
Frequently asked questions
Which Apache Spark resource should I start with?
The Apache Spark mind map is a useful starting point for an overview. It covers architecture, processes, sessions, jobs, stages and tasks. For a more focused start, RDD-based programming looks at RDD creation, while DataFrame covers schemas, row objects and SQL queries on a SparkSession object.
What do the mind maps cover?
The maps cover several parts of Apache Spark. RDD-based programming includes SparkContext and ways to create RDDs. DataFrame covers schemas and queries, while Apache Spark introduces architecture and execution concepts. The Spark map includes RDD transformations such as Map, Filter and Union, along with pair RDD operations.
Are these Apache Spark resources free to use?
Yes. Every resource listed on this page is free to open, study and take without an account. A free account additionally saves your quiz scores and lets you make your own quizzes, mind maps, flashcards and notes. The listed resources were made by GoConqr users.
Who are these resources for?
The page contains resources at university and professional levels. University students and professional candidates can use them to study Spark concepts, RDDs and DataFrames. Teachers looking for ready-made material can also use the maps, notes, flashcards, slides and quiz listed here.