BigMemory Go 4.3.4 | Installation Guide | Configuring BigMemory Go
Configuring BigMemory Go
Automatic Resource Control
Automatic Resource Control (ARC) gives you fine-grained controls for tuning performance and enabling trade-offs between throughput, latency and data access. Independently adjustable configuration parameters include differentiated tier-based sizing and pinning hot or eternal data in the most effective tier.
Dynamically Sizing Stores
Tuning often involves sizing stores appropriately. There are a number of ways to size the different BigMemory Go data tiers using simple configuration sizing attributes. For information on how to tune tier sizing by configuring dynamic allocation of memory and automatic balancing, see "Sizing Storage Tiers" in the BigMemory Go Configuration Guide.
Pinning Data
One of the most important aspects of running an in-memory data store involves managing the life of the data in each BigMemory Go tier. For information on the pinning, expiration, and eviction of data, see "Managing Data Life" in the BigMemory Go Configuration Guide.
Fast Restartability - FRS
BigMemory Go has full fault tolerance, allowing for continuous access to in-memory data after a planned or unplanned shutdown, with the option to store a fully consistent record of the in-memory data on the local disk at all times. For information on data persistence, fast restartability, and using the local disk as a storage tier for in-memory data (both heap and off-heap stores), see "Configuring Fast Restart" in the BigMemory Go Configuration Guide.
Search billions of entries - gigabytes or even terabytes of data - with results returned in less than a second. Data is indexed without significant overhead, and features like "GroupBy', direct support for handling null values, and optimization around handling huge results sets are included. The Search API provides the ability for data to be looked up based on multiple criteria instead of just keys. You can query BigMemory data using either simple SQL statements or the Search API. For more information, see "Searching a Cache" and "Searching with BigMemory SQL" in the BigMemory Go Developer Guide.
Transactional Caching
Transactional modes are a powerful extension for performing atomic operations on data stores, keeping your data in sync with your database. For background and configuration information for BigMemory Go transactional modes, see "Transaction Support" in the BigMemory Go Developer Guide. Explicit locking is another API that can be used as a custom alternative to XA Transactions or Local transactions (see "Using Explicit Locking" in the BigMemory Go Developer Guide).
Administration and Monitoring
The Terracotta Management Console (TMC) is a web-based monitoring and administration application for tuning cache usage, detecting errors, and providing an easy-to-use access point to integrate with production management systems. For more information, see the Terracotta Management Console User's Guide.
As an alternative to the TMC, standard JMX-based administration and monitoring is available. See the BigMemory Go Operations Guide.
For logging, BigMemory Go uses the flexible SLF4J logging framework. See the BigMemory Go Operations Guide.

Copyright © 2010 - 2019 | Software AG, Darmstadt, Germany and/or Software AG USA, Inc., Reston, VA, USA, and/or its subsidiaries and/or its affiliates and/or their licensors.
Innovation Release