Apache Spark: Distributed Processing for Big Data Engineering and ML
Apache Spark is the distributed processing engine for big data — batch ETL (Spark SQL, DataFrames), streaming (Kafka + Spark Structured Streaming), and ML (MLlib). Runs on Databricks, Microsoft Fabric, and cloud-native Spark.
What Is Apache Spark and Where It Runs
Apache Spark processes data distributed across a cluster — Spark SQL for structured queries, DataFrame API for programmatic transformation (PySpark, Scala), Structured Streaming for real-time processing, MLlib for machine learning, and GraphX for graph analytics. Spark handles terabyte-scale data that single-machine tools (Pandas, SQL Server) cannot process.
Enterprise Spark typically runs on managed platforms: Databricks (most popular, Delta Lake integration, Unity Catalog), Microsoft Fabric (Spark notebooks within the unified platform), or cloud-native (Azure HDInsight, AWS EMR, GCP Dataproc). Spark optimization requires: partition strategy, shuffle management, broadcast joins, caching, and the cost/performance tuning that prevents $50K cloud bills from unoptimized Spark jobs.
How Xylity Works With Apache Spark
Consulting, implementation, and specialist talent for Apache Spark projects.
Big Data Engineering
Spark at terabyte scale.
Data Engineering
Spark-powered pipelines.
Data Pipelines
ETL/ELT with PySpark.
Apache Spark Specialists — Deployed in 4.3 Days
Pre-qualified through consulting-led matching. 92% first-match acceptance.
Hire Databricks/Spark Engineers
Pre-qualified. 4.3-day avg.
Hire Data Engineers
Pre-qualified. 4.3-day avg.
Technologies That Work With Apache Spark
Apache Spark FAQ
Xylity provides Apache Spark consulting, implementation, and specialist talent. We cover strategy, architecture, development, and optimization — plus pre-qualified Apache Spark specialists deployed in 4.3 days average through 200+ delivery partners.
Yes. Pre-qualified through 4-stage consulting-led matching. 92% first-match acceptance rate. Senior to architect level.
Apache Spark integrates with multiple technologies. Our consulting-led approach selects the right combination for your requirements — technology-agnostic recommendations based on your data, team, and business goals.
Your Apache Spark Project Needs
The Right Partner
Apache Spark consulting — distributed processing, performance optimization, and platform selection specialists.