Oracle International Corporation

Ankita Kumar

Juan R Loaiza

Tirthankar Lahiri

Garret Frederick Swart

Ajit Mylavarapu

Vasudha Krishnaswamy

Sukhada Pendse

Solmaz Kolahi

Vineet Marwah

Srinivas Vemuri

Sanket Hase

Kam Shergill

Himanshu Chatterjee

One or more engine instances are executed on each host to form an engine cluster. A plurality of control instances are executed on a first set of hosts to form a control cluster and comprise a control instance leader and one or more control instance followers. In response to a first host indicating a failure of a neighbor host, a pair-wise focused investigation is initiated to check peer-to-peer connections between the first host and the neighbor host. In response to one or more additional hosts indicating failures of neighbor hosts while the pair-wise focused investigation is being performed, a wide investigation is performed to check connections between the control cluster and the plurality of hosts. One or more hosts are added to an eviction list and an eviction protocol is performed to evict the one or more hosts from the engine cluster using the eviction list.

System and method for transaction continuity across failures in a scale-out database

A method and apparatus for compression units in an index block is provided. A particular leaf block of a database index for a table is generated. The particular leaf block corresponds to a particular range of key values. A compression scheme is determined for a plurality of index entries with key values within the particular range. A compression unit that includes a plurality of compressed index entries is generated by applying the compression scheme to the plurality of index entries. Compression metadata describing the compression scheme is generated. The compression unit and the compression metadata is stored in the particular leaf block. In response to a request, at least a portion of the compression unit is decompressed to access one or more index entries.

Compression units in an index block

A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to 'slices', and storing multiple copies ('duplicas') of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the &#x201c;primary duplica&#x201d;. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (&#x201c;secondary duplicas&#x201d;) of the same slice.

System and method for high performance multi-statement interactive transactions with snapshot isolation in a scale-out database

Techniques are provided for maintaining and using row-level and column-level invalidation information for a copy of data items stored in-memory via a row-bitmap and column-bitmap. The row-bitmap and column-bitmap can be used to determine whether a database query can be processed using in-memory data or not. The row-bitmap and column-bitmap can thus improve the frequency with which database queries can be processed using in-memory data.

Column level invalidation for in-memory database

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Bellevue, WA, United States of America

Ankita Kumar