Spark as a Service with Azure Databricks
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Presented at: Global Azure Bootcamp (Melbourne) Participants will get a deep dive into one of Azure’s newest offering: Azure Databricks, a fast, easy and collaborative Apache® Spark™ based analytics platform optimized for Azure. In this session, we will go through Azure Databricks key collaboration features, cluster management, and tight data integration with Azure data sources. We’ll also walk through an end-to-end Recommendation System Data Pipeline built using Spark on Azure Databricks.
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Simplilearn’s Apache Spark and Scala certification training are designed to:
1. Advance your expertise in the Big Data Hadoop Ecosystem
2. Help you master essential Apache and Spark skills, such as Spark Streaming, Spark SQL, machine learning programming, GraphX programming and Shell Scripting Spark
3. Help you land a Hadoop developer job requiring Apache Spark expertise by giving you a real-life industry project coupled with 30 demos
What skills will you learn?
By completing this Apache Spark and Scala course you will be able to:
1. Understand the limitations of MapReduce and the role of Spark in overcoming these limitations
2. Understand the fundamentals of the Scala programming language and its features
3. Explain and master the process of installing Spark as a standalone cluster
4. Develop expertise in using Resilient Distributed Datasets (RDD) for creating applications in Spark
5. Master Structured Query Language (SQL) using SparkSQL
6. Gain a thorough understanding of Spark streaming features
7. Master and describe the features of Spark ML programming and GraphX programming
Who should take this Scala course?
1. Professionals aspiring for a career in the field of real-time big data analytics
2. Analytics professionals
3. Research professionals
4. IT developers and testers
5. Data scientists
6. BI and reporting professionals
7. Students who wish to gain a thorough understanding of Apache Spark
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Austin Data Meetup 092014 - Spark
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Building data pipelines for modern data warehouse with Apache® Spark™ and .NE...Michael Rys This presentation shows how you can build solutions that follow the modern data warehouse architecture and introduces the .NET for Apache Spark support (https://dot.net/spark, https://github.com/dotnet/spark)
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4. Components of Apache Spark
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What are the course objectives?
Simplilearn’s Apache Spark and Scala certification training are designed to:
1. Advance your expertise in the Big Data Hadoop Ecosystem
2. Help you master essential Apache and Spark skills, such as Spark Streaming, Spark SQL, machine learning programming, GraphX programming and Shell Scripting Spark
3. Help you land a Hadoop developer job requiring Apache Spark expertise by giving you a real-life industry project coupled with 30 demos
What skills will you learn?
By completing this Apache Spark and Scala course you will be able to:
1. Understand the limitations of MapReduce and the role of Spark in overcoming these limitations
2. Understand the fundamentals of the Scala programming language and its features
3. Explain and master the process of installing Spark as a standalone cluster
4. Develop expertise in using Resilient Distributed Datasets (RDD) for creating applications in Spark
5. Master Structured Query Language (SQL) using SparkSQL
6. Gain a thorough understanding of Spark streaming features
7. Master and describe the features of Spark ML programming and GraphX programming
Who should take this Scala course?
1. Professionals aspiring for a career in the field of real-time big data analytics
2. Analytics professionals
3. Research professionals
4. IT developers and testers
5. Data scientists
6. BI and reporting professionals
7. Students who wish to gain a thorough understanding of Apache Spark
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The registration page: https://bityl.co/7yRK
The promotion page: https://www.facebook.com/groups/awsugtw/permalink/4123481584394988/
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Spark as a Service with Azure Databricks
- 3. • • •
- 7. Apache Spark Core APIs RDDs, DataFrame, Datasets Spark SQL GraphX (graph) Structured Streaming Mllib (machine learning) Spark: The Definitive Guide
- 11. Structured Streaming Advanced Analytics Libraries & Ecosystem Low Level APIs Structure APIs Datasets DataFrame SQL RDDs Distributed Variables
- 13. Transformations Actions select show distinct count groupBy collect sum save orderBy first filter limit summarize … and much more
- 14. Driver Cluster Manager Executor Spark Session User code Executor Executor Distributed Data Structure Partition Partition Partition Partition Partition Partition
- 16. Managed Apache Spark platform optimized for Azure Microsoft Azure
- 19. Optimized Databricks Runtime Engine DATABRICKS I/O SERVERLESS Collaborative Workspace Cloud storage Data warehouses Hadoop storage IoT / streaming data Rest APIs Machine learning models BI tools Data exports Data warehouses AZURE DATABRICKS Enhance Productivity Deploy Production Jobs & Workflows APACHE SPARK MULTI-STAGE PIPELINES DATA ENGINEER JOB SCHEDULER NOTIFICATION & LOGS DATA SCIENTIST BUSINESS ANALYST Build on secure & trusted cloud Scale without limits
- 20. Cosmos DB Kafka on HDInsight Event Hubs Power BI SQL DW Data Factory O R C H E S T R A T I O N Storage (Azure) Azure Data Lake S T O R A G E I N G E S T V I S U A L I Z E S E C U R E Azure Active Directory A Z U RE DATA BRIC KS
- 25. https://movielens.org/ F. Maxwell Harper and Joseph A. Konstan. 2015. The MovieLens Datasets: History and Context. ACM Transactions on Interactive Intelligent Systems (TiiS) 5, 4, Article 19 (December 2015), 19 pages. DOI=http://dx.doi.org/10.1145/2827872
- 27. Apache Spark Core APIs RDDs, DataFrame, Datasets Spark SQL GraphX (graph) Structured Streaming Mllib (machine learning)
- 29. Apache Spark Core APIs RDDs, DataFrame, Datasets Spark SQL GraphX (graph) Structured Streaming Mllib (machine learning)
- 32. Apache Spark Core APIs RDDs, DataFrame, Datasets Spark SQL GraphX (graph) Structured Streaming Mllib (machine learning)
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