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Information about using DataStax Enterprise for Administrators.
DataStax Enterprise release notes cover cluster requirements, upgrade guidance, components, security updates, changes and enhancements, issues, and resolved issues for DataStax Enterprise 5.1.
DataStax Enterprise can be installed in a number of ways, depending on the purpose of the installation, the type of operating system, and the available permissions.
Information about configuring DataStax Enterprise, such as recommended production setting, configuration files, snitch configuration, start-up parameters, heap dump settings, using virtual nodes, and more.
Initializing a DataStax Enterprise cluster includes configuring, and choosing how the data is divided across the nodes in the cluster.
DataStax Enterprise 5.1 Security Guide.
Information on using DSE Analytics, DSEFS, DSE Search, DSE Graph, DSE Advanced Replication, DSE In-Memory, DSE Multi-Instance, DSE Tiered Storage and DSE Performance services.
DataStax Enterprise 5.1 Analytics includes integration with Apache Spark.
DSE Search is part of DataStax Enterprise (DSE). DSE Search allows you to find data and create features like product catalogs, document repositories, and ad-hoc reports. See DSE Search architecture.
Documentation for developers and administrators on installing, configuring, and using the features and capabilities of DSE Graph.
DSE Management Services automatically handle administration and maintenance tasks and assist with overall database cluster management.
The DSE Performance Service automatically collects and organizes performance diagnostic information into a set of data dictionary tables that can be queried with CQL.
Steps to configure the Performance Service replication strategy.
Tasks to enable and configure collection of data using the Performance Service.
Edit dse.yaml to enable and configure collection of search data.
Steps to help you identify slow search queries using the DataStax Enterprise Performance Service.
Steps to enable logging of object records errors that occur during document indexing.
Enable the solr_latency_snapshot_options parameter in dse.yaml and set the other options as required.
Enable the solr_cache_stats_options parameter in dse.yaml and set the other options as required.
Steps to enable collecting index statistics.
Enable the solr_update_handler_metrics_options parameter in dse.yaml and set the other options as required.
How to enable the solr_request_handler_metrics_options parameter in dse.yaml and set options.
Performance data is stored in a table to allow you to monitor and tune Spark analytics jobs.
A complete listing and brief description of DSE Performance Service diagnostic tables.
FAQs about using, and log information, snapshot, statistics in the DSE Search Performance Service diagnostic tables.
This OpsCenter service scans DataStax Enterprise clusters and automatically detects issues that threaten the cluster’s security, availability or performance.
This OpsCenter service accumulates cluster health and resource utilization metrics to perform historical trend analysis. This process helps you understand cluster performance over time, and includes powerful forecasting capabilities to predict future usage and growth.
This OpsCenter service performs repair operations in the background across a DataStax Enterprise cluster with minimal impact. This process alleviates the potential performance impact of having to periodically run repair on entire nodes.
Documentation for configuring and using configurable distributed data replication.
DataStax Enterprise includes DSE In-Memory for storing data to and accessing data exclusively from memory.
Documentation for running multiple DataStax Enterprise nodes on a single host machine.
Documentation for automating smart data movement across different types of storage media.
Tools include nodetool, dse commands, dsetool, cfs-stress tool, pre-flight check and yaml_diff tools, and the sstableloader.
DataStax Enterprise operation topics, such as node and datacenter operations, changing replication strategies, configuring compaction and compression, caching, and tuning Bloom filters.
Hardware selection, estimating disk capacity, anti-patterns, cluster testing and more.