An interface which declares the keys for the map returned by
Environment variables understood by the
Class has a static method which writes a copyright banner on stdout once per JVM.
A class for those few statics that it makes sense to reference from other places.
Aggregates test suites in increase dependency order.
bigdata® is a scale-out data and computing fabric designed for commodity hardware. Scale-out is achieved using key-range partitioned B+Trees and distributed computing. The architecture supports both embedded and scale-out database applications. Unisolated transactions are supported and provide for extremely high read-write concurrency when used as a sparse row store. In addition, both read-committed, read-only, and fully isolated read-write transactions are supported using Multi-Version Concurrency Control (MVCC).
The bigdata architecture is broken down into several services:
Note: Readers familar with Google's research publications or with the Apache Hadoop effort will recognize some similarities and some differences. For example, both Google and Hadoop both use a distributed file system for failover. While bigdata may be deployed in a similar manner using a third party distributed file system, it also offers a store-level media replication strategy for addressing failover.
offsetat which the a record was written and the
lengthof the record.
BTreesupports variable length byte keys, a copy-on-write strategy for nodes and leaves which is used to support transactional isolation, and remains balanced under both insert and delete operations. a B+Tree may be exported into a read-only
IndexSegmentusing an efficient bulk index build utility.
com.bigdata.isolation.IValueobjects wrapping application data values. Each
com.bigdata.isolation.IValueencapsulates a version counter, which is used to detect write-write conflicts, and a deleted flag, which is used to mark keys that have been deleted until a full compacting merge can be performed.
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