Agenda Introduction Setup Python REPL Basic Programming Constructs Functions and Lambda Functions Collections— List, Set, Dict Basic Map Reduce operations Basic 1/0 operations Introduction Python is interpreter based programming language Adaptability of Python is very high in Data Engineering and Data Science fields Spark APIs are well integrated with Python Highly relevant for Cloudera and …
If Hive and Spark are integrated, we can create data frames from data in Hive tables or run Spark SQL queries against it. We can use spark.read.table to read data from Hive tables into Data Frame We can prefix database name to table name while reading Hive tables into Data Frame We can also run …
Let us see how we can read text data from files into a data frame. spark.read also have APIs for other types of file formats, but we will get into those details later. We can use spark.read.csv or spark.read.text to read text data. spark.read.csv can be used for comma separated data. Default field names will …
Let us understand the execution modes as well as different components of the Spark Framework. Also, we will recap some important aspects of YARN. Execution Modes Following are the different execution modes supported by Spark. Local (for development) Standalone (for development) Mesos YARN As our cluster uses YARN, let us recap some important aspects of …
Let us start with a simple application to understand details related to architecture using pyspark. As we have multiple versions of Spark on our lab and we are exploring Spark 2 we need to export SPARK_MAIOR_VERSION with 2. For this demo, we will disable dynamic allocation by setting spark. dynamicAllocation.enabled to false. Launch pyspark using …
We need to deal with 2 types of data structures in Spark – RDD and Data Frames. We will see both in detail as we proceed further. RDD is there for quite some time and it is the low-level data structure which spark uses to distribute the data between tasks while data is being processed. …
