MarkLogic Connector for Apache Spark

The MarkLogic Connector for Apache Spark makes it fast and easy to implement Spark jobs for ingesting and exporting data from a MarkLogic Data Hub.

Apache Spark is an in-memory, distributed data processing engine for analytical applications, including machine learning, SQL, streaming, and graph. As a unified analytical tool, it is primarily used by developers like data engineers and data scientists to build scalable data pipelines that span diverse data sources like Object Stores, RDBMS, HDFS, NoSQL etc.

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Major Benefits

• Scalable Ingestion: Build data pipelines to load data as is from any data source while tracking provenance and lineage metadata.
• Secure Sharing: Use MarkLogic’s multi-model querying capabilities to securely share fit-for-purpose data with Spark libraries for complex analytical use-cases including machine learning and AI

Getting Started

Step through the written tutorial for Spark connector to get started ingesting and exporting.