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DSE 6.7 Administrator Guide Latest DSE version Latest 6.7 patch: 6.7.7

Getting started
Release notes
Installing
Configuration
Initializing a cluster
Security
DSE advanced functionality
Tools
Operations
Planning

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DSE advanced functionality
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.
DSE Search
DSE Search allows you to quickly find data and provide a modern search experience for your users, helping you create features like product catalogs, document repositories, ad-hoc reporting engines, and more.
Performance tuning and monitoring
Tune DSE Search in the event of performance degradation, high memory consumption, or other problems.

DSE advanced functionality
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.
- DSE Analytics
  DataStax Enterprise 6.7 Analytics includes integration with Apache Spark.
- DSE Search
  DSE Search allows you to quickly find data and provide a modern search experience for your users, helping you create features like product catalogs, document repositories, ad-hoc reporting engines, and more.
  - About DSE Search
    DSE Search simplifies using search applications for data stored in a database.
  - Configuring DSE Search
    DSE Search logging, search index configuration, reference information and so on.
  - Performance tuning and monitoring
    Tune DSE Search in the event of performance degradation, high memory consumption, or other problems.
    - Tuning search for maximum indexing throughput
      Tuning DSE Search for maximum indexing throughput
    - Resolving query timeouts on restarted nodes
      Steps to fix query timeouts when restarting nodes with large search indexes.
    - Table compression can optimize reads
      Configure data compression on a per-table basis to optimize performance of read-dominated tasks.
    - Parallelizing large row reads
      Configure DSE Search to parallelize the retrieval of a large number of rows to improve performance.
    - Changing the stack size and memtable space
      Change the stack size to improve performance under Tomcat.
    - Tuning index size and range query speed
      Advanced users can change the precision step of special token field types to tune index size.
    - Improving read performance
      Steps to increase DSE Search read performance.
  - DSE Search operations
    You can run DSE Search on one or more nodes. Typical operations including configuration of nodes, policies, query routing, balancing loads, and communications.
  - Solr interfaces
  - HTTP API SolrJ and other Solr clients
    Apache Solr clients work with DataStax Enterprise. DataStax has extended SolrJ to protect internal Solr communication and HTTP access using SSL.
- DSE Graph
  Documentation for developers and administrators on installing, configuring, and using the features and capabilities of DSE Graph.
- DSE Management Services
  DSE Management Services automatically handle administration and maintenance tasks and assist with overall database cluster management.
- NodeSync service
  Continuous background repair that virtually eliminates manual efforts to run repair operations in a DataStax cluster.
- DSE Advanced Replication
  Documentation for configuring and using configurable distributed data replication.
- DSE In-Memory
  DataStax Enterprise includes DSE In-Memory for storing data to and accessing data exclusively from memory.
- DSE Multi-Instance
  Documentation for running multiple DataStax Enterprise nodes on a single host machine.
- DSE Tiered Storage
  Documentation for automating smart data movement across different types of storage media.

DSE Search performance tuning and monitoring

Tune DSE Search in the event of performance degradation, high memory consumption, or other problems.

Use these tuning options for DSE Search:

Tuning search for maximum indexing throughput
Tuning DSE Search for maximum indexing throughput
Resolving query timeouts on restarted nodes
Steps to fix query timeouts when restarting nodes with large search indexes.
Table compression can optimize reads
Configure data compression on a per-table basis to optimize performance of read-dominated tasks.
Parallelizing large row reads
Configure DSE Search to parallelize the retrieval of a large number of rows to improve performance.
Changing the stack size and memtable space
Change the stack size to improve performance under Tomcat.
Tuning index size and range query speed
Advanced users can change the precision step of special token field types to tune index size.
Improving read performance
Steps to increase DSE Search read performance.

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Build time: 2020-03-16 16:24:28.438

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Apache, Apache Cassandra, Cassandra, Apache Tomcat, Tomcat, Apache Lucene, Apache Solr, Apache Hadoop, Hadoop, Apache Spark, Spark, Apache TinkerPop, TinkerPop, Apache Kafka and Kafka are either registered trademarks or trademarks of the Apache Software Foundation or its subsidiaries in Canada, the United States and/or other countries.

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