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Apache Spark Certification Training
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About Course
The Apache Spark Online Training program is designed to help learners master one of the most powerful big data processing frameworks used for large-scale data analytics and real-time processing. Apache Spark provides lightning-fast cluster computing and is widely used in data engineering, data science, and AI-driven applications.
This course covers key Spark components such as Apache Spark Core, Spark SQL, Apache Spark Streaming, and MLlib (Machine Learning Library). You’ll learn how to process massive datasets efficiently, perform data transformations, and build real-time analytics pipelines using Python (Apache Spark), Scala, or Java.
Through hands-on labs and real-time projects, participants will gain practical experience in managing distributed data processing, integrating Apache Spark with Hadoop and other big data tools, and optimizing performance for large-scale applications.
By the end of the course, you’ll be ready to work as a Big Data Engineer, Apache Spark Developer, or Data Analyst, capable of designing and implementing high-performance data processing solutions.
Apache Spark Training Course Syllabus
Spark and Azure DataBricks Architecture
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Mounting ADLS with Azure Data Bricks
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RDDs
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DataFrames
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Parallelize () and repartition
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Struct Type and Struct Field
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Select, With column and with column renamed
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Collect
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UDF
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Join()
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Dataframe Operations
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Reading different Files
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Pyspark SQL Functions
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Mounting to Databricks
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Cluster Types and setting up the clusters
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Pyspark Built-in Functions
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Cosmos DB connectivity with Azure Databricks
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Apache Spark Course Key Features
- Live Instructor based training with software
- Certification Oriented content
- Hands-on complete Realtime training
- Flexible schedule demo's & classes
- Live recorded videos access
- Study material provided
- JOB Assistance
Course completion certificate
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Live Virtual Training
- Schedule your sessions at your comfortable with timings
- Instructor-Led training real time projects
- Certification Guidance
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Self-Paced Learning
- Complete set of live-online training session recorded videos.
- Learn technology at your own pace.
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- Learn as a full day schedule with discussions, exercises.
- Practical use cases.
- Design your own syllabus based
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Apache Spark Online Training FAQ'S
What is PySpark in the context of Azure Databricks?
PySpark is the Python library for Apache Spark, and when used in Azure Databricks, it enables distributed big data processing and machine learning in the cloud.
Why is Azure Databricks a preferred platform for PySpark?
Azure Databricks provides a scalable, collaborative workspace with optimized clusters, making PySpark development and deployment efficient for real-time analytics.
What are PySpark DataFrames and their benefits?
DataFrames are high-level abstractions for structured data that support SQL-like operations, enabling easier data manipulation and better performance.
How does PySpark process real-time streaming data?
Using Structured Streaming, PySpark ingests and processes continuous data streams, useful for IoT, financial, and event-driven applications.
How does Azure Data Lake integrate with Azure Databricks and PySpark?
Azure Data Lake provides scalable storage, and Databricks with PySpark uses connectors or mounts to process both structured and unstructured datasets efficiently.
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