Apache Spark - Unified Engine for Large-Scale Data Analytics

Apache Spark Unified Engine for Large-Scale Data Analytics

Free

#data engineering
#Data Science
#Machine Learning
#SQL
#Python
#Scala

What is Apache Spark?

Apache Spark™ is a multi-language engine designed for data engineering, data science, and machine learning. It can operate on single-node machines or clusters. The engine supports batch and streaming data processing using a variety of languages such as Python, SQL, Scala, Java, and R.

Spark features an advanced distributed SQL engine, allowing users to execute fast, distributed ANSI SQL queries. This capability makes it suitable for dashboarding and ad-hoc reporting, often outperforming traditional data warehouses. Spark also provides data science at scale by enabling Exploratory Data Analysis (EDA) on petabyte-scale datasets.

Features

Batch/streaming data: Unify the processing of your data in batches and real-time streaming.
SQL analytics: Execute fast, distributed ANSI SQL queries for dashboarding and ad-hoc reporting.
Data science at scale: Perform Exploratory Data Analysis (EDA) on petabyte-scale data.
Machine learning: Train machine learning algorithms and scale to fault-tolerant clusters.
Adaptive Query Execution: Adapts the execution plan at runtime.
Support for ANSI SQL: Use the same SQL you're already comfortable with.
Structured and unstructured data: Works on structured tables and unstructured data such as JSON or images.

Use Cases

Dashboarding and ad-hoc reporting
Exploratory Data Analysis (EDA) on large datasets
Machine learning model training and deployment
Processing data in batches
Real-time streaming data

FAQs

What is Apache Spark™?

Apache Spark™ is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.