Spark scala dataframe api
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Understand Spark's data caching and its usage. Understand performance implications and optimizations when using Spark. Be familiar with Spark Graph Processing and SparkML machine learning. Outline. Scala Ramp Up (Optional) Scala Introduction, Variables, Data Types, Control Flow. The Scala Interpreter. Collections and their Standard Methods (e.g ...
[DOCX File]files.transtutors.com
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Objectives. Gain in depth experience playing around with big data tools (Hive, SparkRDDs, and Spark SQL). Solve challenging big data processing tasks by finding highly efficient s
[DOCX File]Abstract - Virginia Tech
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Moreover, another challenge we faced is an incompatible Cloudera version with some of our tools - namely ArchiveSpark. Unfortunately, in its current state the DLRL CDH Hadoop cluster hosts one of the older versions of Spark (Version 1.5.0) whereas the ArchiveSpark library leverages some of the API only present in Spark 1.6.1 onwards.
[DOC File]Sangeet Gangishetty
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Experienced in handling large datasets using Partitions, Spark in Memory capabilities, Broadcasts in Spark, Effective & efficient Joins, Transformations and other during ingestion process itself. Spark DataFrame API’s and Scala Case class to process GB’s of Dataset
[DOCX File]tipdm.com
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5.分布式文件系统HDFS Java API实战：创建目录，上传，下载，删除； ... 4.Spark编程基础（Scala及编程简介）； ... 4.2掌握DataFrame的常用操作 ...
[DOC File]Notes on Apache Spark 2 - The Risberg Family
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The distribution includes the core libraries, the Scala, Java, and Python API’s, a large set of examples, and the Shark, Streaming, and machine learning libraries. Prior to 2017, we have been primarily working with the Scala API’s. Spark is similar to Hadoop in ecosystem structure.
[DOCX File]Table of Tables - Virginia Tech
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The plotly offline API allows for the writing of richly linked and annotated visualizations to HTML files. Plotly graphs tend to consist of three parts: traces, layouts, and figures. Traces are subsets of a Dataframe and contain data for a single aspect of a plot, such as a …
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