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Splunk Hadoop Connect provides bi-directional integration to easily and reliably move data between Splunk and Hadoop. Deploy Splunk quickly for real-time collection, indexing, analysis and visualizations and then reliably forward events to Hadoop for long-term archiving and additional batch analytics. You can further leverage Splunk by importing data already stored in Hadoop. This makes it easy to stand up reliable, secure, enterprise-grade big data projects in days instead of months.

Splunk Hadoop Connect includes three core features:

Export events to Hadoop - Use Splunk to collect and index massive streams of machine data in real-time. Then send all or a subset of events in a reliable and predictable way to HDFS for archiving, further processing or additional batch analytics. You can choose to pre-process data in Splunk before exporting the results into Hadoop, selecting both the format type as well as specific fields to include. Alternatively, you can simply export raw events.
Explore Hadoop directories and files - Browse, navigate and inspect HDFS directories and files from the Splunk Hadoop Connect user interface before deciding to import them into Splunk.
Import and Index Hadoop data into Splunk - Import and index Hadoop data into Splunk to make it available for searching, reporting, analysis and visualizations and provide role-based access controls protection. Gain rapid insight and analysis without writing MapReduce code.

Splunk Hadoop Connect Video Tutorials:

Splunk Hadoop Connect is compatible with Apache Hadoop; it is also tested and certified against Cloudera's CDH and Hortonworks' HDP distribution. Additionally, Hadoop Connect supports any locally mounted point, which enables it to work with MapR or IBM GPFS distributions. Refer to the product documentation for the latest list of supported Hadoop distributions.

Splunk Hadoop Connect

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