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Udemy - A Big Data Hadoop and Spark project for absolute beginners

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Udemy - A Big Data Hadoop and Spark project for absolute beginners (Size: 3.7 GB)
  0 0 B
  1. Advanced Spark datasets.mp4 12.6 MB
  1. Big Data concepts.mp4 19.7 MB
  1. Creating a free Hadoop and Spark cluster using Google Dataproc.mp4 79.2 MB
  1. Exporting the project to an uber jar.mp4 45.9 MB
  1. Fast queries with Hive Partitioning.mp4 116.7 MB
  1. Ingesting data from Hive.mp4 43.3 MB
  1. Introduction to AWS data lake use case.mp4 13.6 MB
  1. Introduction.mp4 14.6 MB
  1. Organizing code further.mp4 21.1 MB
  1. Project - Bank prospects marketing data transformation using Hadoop and Spark.mp4 87.8 MB
  1. PySpark Hadoop Hive development environment using PyCharm and Winutils.mp4 97.5 MB
  1. Python Logging.mp4 42 MB
  1. Python unittest framework.mp4 23.4 MB
  1. Reading from Hive and Writing to Postgres.mp4 104.1 MB
  1. Scala Unit Testing using JUnit & ScalaTest.mp4 62.4 MB
  1. Scala basics.mp4 54.8 MB
  1. Spark Scala real world coding introduction.mp4 2.5 MB
  1. Spark concepts.mp4 28.1 MB
  1. Structured Streaming concepts.mp4 6.1 MB
  1 190.4 KB
  1.1 DataPipeline_v5.zip 1.5 KB
  1.1 FutureXScalaUnitTesting.zip 15.6 KB
  1.1 FutureXSparkScalaProject_readHivewritePG.zip 353.5 KB
  1.1 advanced_spark_datasets.zip 736.2 KB
  1.1 hello_world_python_spark_hadoop.zip 716 B
  1.1 hive-partition.txt 2.3 KB
  1.1 pom.zip 1 KB
  1.1 pyspark_bank_marketing_project.py 2.7 KB
  1.1 scala-basics.txt 1.9 KB
  1.1 test.zip 409 B
  1.2 pyspark_bank_marketing_project.zip 14.7 KB
  1.2 retailstore_large.zip 5.4 MB
  10. Installing PostgreSQL.mp4 32.8 MB
  10.1 Postgres-course-catalog.sql 1.2 KB
  11. psql command line interface for PostgreSQL.mp4 11 MB
  11.1 Postgres-course-catalog_psql.zip 614 B
  12. Fetching PostgresSQL data to a Spark DataFrame.mp4 31.8 MB
  12.1 FutureXSparkScalaProject_Postgres.zip 12.3 KB
  13. Importing a project into IntelliJ.mp4 34.2 MB
  14. Organizing code with Objects and Methods.mp4 91.2 MB
  14.1 FutureXSparkScalaProject_organize.zip 108.7 KB
  15. Implementing Log4j SLf4j Logging.mp4 43.3 MB
  15.1 log4j.zip 307 B
  16. Exception Handling with try, catch, Option, Some and None.mp4 54.8 MB
  2. AWS data lake - S3, Glue and Athena introduction.mp4 24.5 MB
  2. Cloudera QuickStart VM Installation on GCP.mp4 66.1 MB
  2. Fast queries with Hive Bucketing.mp4 21 MB
  2. Hadoop concepts.mp4 41.2 MB
  2. Installing JDK on a local Machine.mp4 12.7 MB
  2. Installing Spark on Google Colab.mp4 35.4 MB
  2. Managing log level through a configuration file.mp4 76.7 MB
  2. Rapid Revision - Big Data, Hadoop and Spark concepts.mp4 108.7 MB
  2. Reading Configuration from JSON using Typesafe.mp4 85.1 MB
  2. Reading configuration from a property file.mp4 19.4 MB
  2. Spark SQL DataFrame using Scala.mp4 35 MB
  2. Spark Transformation unit testing using ScalaTest.mp4 73.3 MB
  2. Storing data in HDFS and querying with Hive.mp4 82.1 MB
  2. Streaming data from files.mp4 18.8 MB
  2. Structuring code with classes and methods.mp4 31.7 MB
  2. Transforming ingested data.mp4 18.7 MB
  2. Unit testing PySpark transformation logic.mp4 31.9 MB
  2 4.2 KB
  2. User Defined Function (UDF).mp4 29.8 MB
  2.1 Creating a Data Lake using S3, Glue, Athena.zip 1.4 KB
  2.1 DataPipeline_logging_1.zip 2.6 KB
  2.1 DataPipeline_read_config.zip 918 KB
  2.1 DataPipeline_v1.zip 921 B
  2.1 FutureXSparkScalaProject_ScalaTest.zip 980.5 KB
  2.1 FutureXSparkScalaProject_typesafe_config_parser.zip 358.9 KB
  2.1 Spark_Installation_on_Colab.zip 11.9 KB
  2.1 cloudera-gcp.txt 3.4 KB
  2.1 files.zip 512 B
  2.1 hive-bucketing.txt 1.2 KB
  2.1 pyspark_udf_and_join.py 3.7 KB
  2.1 retailstore.csv 307 B
  2.1 spark-scala-dataframe.txt 2.5 KB
  2.2 FuturexMiscSparkScala.zip 18.7 KB
  2.2 PySpark_udf_and_join.zip 16 KB
  2.2 hive-hdfs-commands.txt 1.5 KB
  2.2 retailstore_large.zip 5.4 MB
  2.2 spark_installation_on_colab.py 1.3 KB
  3. Bank prospects marketing project in Scala.mp4 22.5 MB
  3. Batch Vs Streaming code.mp4 12.6 MB
  3. Create a data lake on AWS S3.mp4 15.6 MB
  3. Having custom logger for each Python class.mp4 42 MB
  3. How Spark works.mp4 7.5 MB
  3. Installing IntelliJ IDEA.mp4 5.2 MB
  3. Installing PostgreSQL.mp4 23.3 MB
  3. Joins - Left, Right, Inner, Outer.mp4 50 MB
  3. Python basics.mp4 71.3 MB
  3. Running Spark 2 with Hive on Cloudera QuickStart VM.mp4 36.6 MB
  3. Unit testing an error.mp4 12.9 MB
  3. Writing data to a Hive Table.mp4 31.2 MB
  3 71.3 KB
  3. Unit testing to catch an Exception.mp4 17.6 MB
  3.1 DataPipeline_Logger2.zip 2.8 KB
  3.1 FutureXSparkScalaProject_writeToHive.zip 396.9 KB
  3.1 Postgres-course-catalog.zip 614 B
  3.1 PySpark_udf_and_join.zip 16 KB
  3.1 python_basics.py 4.4 KB
  3.1 spark-scala-bank-marketing-project.txt 1.3 KB
  3.1 spark2-cloudera.txt 1.5 KB
  3.1 test_transformer.zip 819 B
  3.2 pyspark_udf_and_join.py 3.7 KB
  3.2 python_basics.py 4.4 KB
  4. AWS Glue crawler and AWS Athena query tool.mp4 41.9 MB
  4. Adding Scala Plugin to IntelliJ.mp4 2.6 MB
  4. Catching Exception using assertThrows.mp4 23.4 MB
  4. Creating and reusing SparkSession.mp4 53.5 MB
  4. Error Handling with try except and raise.mp4 53 MB
  4. Managing input parameters using a Scala Case Class.mp4 34.3 MB
  4. PySpark - spark submit.mp4 13 MB
  4. PySpark PostgreSQL interaction with Psycopg2 adapter.mp4 59.5 MB
  4. PySpark RDD.mp4 78.5 MB
  4. Uber Jar spark-submit on Cloudera QuickStart VM.mp4 25 MB
  4. Writing streaming data to a Hive table.mp4 24.4 MB
  4.1 DataPipeline_psycopg2.zip 2.4 KB
  4.1 DataPipeline_v2.zip 1.2 KB
  4.1 FutureXSparkScalaProject.zip 978.1 KB
  4.1 files (1).zip 512 B
  4.1 pyspark_rdd.zip 15.7 KB
  4.1 spark-submit.txt 204 B
  4.2 FutureXSparkScalaProject-spark-submit.zip 26.5 KB
  4.2 FuturexMiscSparkScala (1).zip 18.7 KB
  4.2 retailstore.csv 307 B
  5. Doing spark-submit locally.mp4 26.5 MB
  5. ETL transformation using AWS Glue.mp4 48.5 MB
  5. Hello World Scala.mp4 35.1 MB
  5. Intellij Maven troubleshooting tips.html 614 B
  5. PySpark - Spark SQL and DataFrame.mp4 69.4 MB
  5. Spark DataFrame.mp4 44.5 MB
  5. Spark PostgreSQL interaction with JDBC driver.mp4 34.6 MB
  5. Streaming Aggregation.mp4 38.7 MB
  5. Throwing Custom Error and Intercepting Error Message.mp4 60.3 MB
  5.1 DataPipeline_postgres_jdbc.zip 911.8 KB
  5.1 DataPipeline_v3.zip 1.5 KB
  5.1 ScalaHelloWorld.zip 8 KB
  5.1 SparkTransformerSpec.zip 716 B
  5.1 StructuredStreamingWindowAggregation.zip 819 B
  5.1 pyspark_dataframe.py 4.5 KB
  5.2 FutureXSparkScalaProject_assetThrowsIntercept.zip 1 MB
  5.2 PySpark_DataFrame.zip 17.7 KB
  5.2 sale.zip 512 B
  6. Filtering Stream.mp4 44.8 MB
  6. Persisting transformed data in PostgreSQL.mp4 18.8 MB
  6. Running PySpark on a Hadoop Cluster.mp4 45.4 MB
  6. Scala basics using IntelliJ.mp4 75.5 MB
  6. Separating out Ingestion, Transformation and Persistence code.mp4 46 MB
  6. Testing with assertResult.mp4 13 MB
  6. Triggering AWS Glue job with a serverless AWS Lambda function.mp4 57.8 MB
  6.1 DataPipeline_v4.zip 1.7 KB
  6.1 FuturexMiscSparkScala_Filter.zip 33.7 KB
  6.1 ScalaBasics.zip 12.2 KB
  6.1 SparkTransformerSpec.zip 819 B
  6.1 Triggering AWS Glue job with a serverless Lambda function.zip 512 B
  6.1 pg_course.zip 307 B
  6.1 spark-hadoop-commands.txt 1.8 KB
  6.2 persist_transformed_df.zip 819 B
  7. Adding timestamp to streaming data.mp4 30.7 MB
  7. Hello World Spark Scala using IntelliJ.mp4 41.4 MB
  7. Project - Bank prospects data transformation using S3, Glue & Athena services.mp4 76.2 MB
  7. Testing with Matchers.mp4 12.1 MB
  7.1 SparkHelloWorld.zip 9.7 KB
  7.1 StructuredStreamingDemoTimestamp.zip 716 B
  7.1 common.zip 1.7 KB
  7.1 glue_pyspark_bank_marketing_project.zip 1.2 KB
  8. Aggregation in a time window.mp4 37.6 MB
  8. Configuring HADOOP HOME on Windows using Winutils.mp4 8.1 MB
  8. Failing tests intentionally.mp4 10.8 MB
  8.1 StructuredStreamingWindowAggregation.zip 819 B
  8.1 failtests.txt 102 B
  8.1 githuhb-link.txt 0 B
  8.2 winutils.zip 36.1 KB
  9. Enabling Hive Support in Spark Session.mp4 46.3 MB
  9. Sharing fixtures.mp4 10.9 MB
  9. Tumbling window and Sliding window.mp4 9.4 MB
  9.1 FutureXSparkScalaProject.zip 11.7 KB
  9.1 FuturexMiscSparkScala.zip 7.8 KB
  9.1 SparkTransformerSpec.zip 819 B
  TutsNode.com.txt 102 B
  [TGx]Downloaded from torrentgalaxy.to .txt 614 B
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  ▲ 270 total files

Description



Description

Get started with Big Data quickly leveraging free cloud cluster and solving a real world use case! Learn Hadoop, Hive , Spark (both Python and Scala) from scratch!

Learn to code Spark Scala & PySpark like a real world developer. Understand real world coding best practices, logging, error handling , configuration management using both Scala and Python.

Project

A bank is launching a new credit card and wants to identify prospects it can target in its marketing campaign.

It has received prospect data from various internal and 3rd party sources. The data has various issues such as missing or unknown values in certain fields. The data needs to be cleansed before any kind of analysis can be done.

Since the data is in huge volume with billions of records, the bank has asked you to use Big Data Hadoop and Spark technology to cleanse, transform and analyze this data.

What you will learn :

Big Data, Hadoop concepts
How to create a free Hadoop and Spark cluster using Google Dataproc
Hadoop hands-on – HDFS, Hive
Python basics
PySpark RDD – hands-on
PySpark SQL, DataFrame – hands-on
Project work using PySpark and Hive
Scala basics
Spark Scala DataFrame
Project work using Spark Scala
Spark Scala Real world coding framework and development using Winutil, Maven and IntelliJ.
Python Spark Hadoop Hive coding framework and development using PyCharm
Building a data pipeline using Hive , PostgreSQL, Spark
Logging , error handling and unit testing of PySpark and Spark Scala applications
Spark Scala Structured Streaming
Applying spark transformation on data stored in AWS S3 using Glue and viewing data using Athena

Prerequisites :

Some basic programming skills
Some knowledge of SQL queries

Who this course is for:

Beginners who want to learn Big Data or experienced people who want to transition to a Big Data role
Big data beginners who want to learn how to code in the real world

Requirements

Students should have some programming background and some knowledge of SQL queries.

Last Updated 12/2020

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