Oracle International Corporation

Poojan Kumar

Umesh Panchaksharaiah

Juan R Loaiza

Kiran Badrinarain Goyal

Bharat C V Baddepudi

Tirthankar Lahiri

Kothanda Umamageswaran

Hakan Jakobsson

Dmitry Mikhailovich Potapov

Alexander Tsukerman

Selcuk Aya

Nilesh Choudhury

Boris Erlikhman

Sue-Kyoung Lee

Yiu Woon Lau

Susy Fan

Timothy L Shetler

Arvind Nithrakashyap

Kant C Patel

Brian Hirano

Techniques are provided for using an intermediate cache to provide some of the items involved in a scan operation, while other items involved in the scan operation are provided from primary storage. Techniques are also provided for determining whether to service an I/O request for an item with a copy of the item that resides in the intermediate cache based on factors such as a) an identity of the user for whom the I/O request was submitted, b) an identity of a service that submitted the I/O request, c) an indication of a consumer group to which the I/O request maps, d) whether the I/O request is associated with an offloaded filter provided by the database server to the storage system, or e) whether the intermediate cache is overloaded. Techniques are also provided for determining whether to store items in an intermediate cache in response to the items being retrieved, based on logical characteristics associated with the requests that retrieve the items.

Selectively reading data from cache and primary storage based on whether cache is overloaded

Techniques are provided for using an intermediate cache to provide some of the items involved in a scan operation, while other items involved in the scan operation are provided from primary storage. Techniques are also provided for determining whether to service an I/O request for an item with a copy of the item that resides in the intermediate cache based on factors such as a) an identity of the user for whom the I/O request was submitted, b) an identity of a service that submitted the I/O request, c) an indication of a consumer group to which the I/O request maps, or d) whether the intermediate cache is overloaded. Techniques are also provided for determining whether to store items in an intermediate cache in response to the items being retrieved, based on logical characteristics associated with the requests that retrieve the items.

Selectively reading data from cache and primary storage

Processing resources at a storage system for a database server are utilized to perform aspects of a join operation that would conventionally be performed by the database server. When requesting a range of data units from a storage system, the database server includes join metadata describing aspects of the join operation for which the data is being requested. The join metadata may be, for instance, a bloom filter. The storage system reads the requested data from disk as normal. However, prior to sending the requested data back to the storage system, the storage system analyzes the raw data based on the join metadata, removing a certain amount of data that is guaranteed to be irrelevant to the join operation. The storage system then returns filtered data to the database server. The database system thereby avoids the unnecessary transfer of certain data between the storage system and the database server.

Hash join using collaborative parallel filtering in intelligent storage with offloaded bloom filters

Allocation of memory is optimized across multiple pools of memory, based on minimizing the time it takes to successfully retrieve a given data item from each of the multiple pools. First data is generated that indicates a hit rate per pool size for each of multiple memory pools. In an embodiment, the generating step includes continuously monitoring attempts to access, or retrieve a data item from, each of the memory pools. The first data is converted to second data that accounts for a cost of a miss with respect to each of the memory pools. In an embodiment, the second data accounts for the cost of a miss in terms of time. How much of the memory to allocate to each of the memory pools is determined, based on the second data. In an embodiment, the steps of converting and determining are automatically performed, on a periodic basis.

Techniques for automated allocation of memory among a plurality of pools

A method for starting up a database system, comprising allocating memory spaces for three buffers; initializing two of the buffers; partially initializing the third buffer where the third buffer is larger than the other two; instructing the memory manager to initialize the remainder of the third buffer in the background process; performing recovery operations; and opening the database system for use. The database is operated in an open phase while the remainder of the third buffer is initialized in the background and ran in parallel to the recovery operation that may extend beyond the completion of opening the database. Thus opening the database prior to completion of full initialization and initializing the third buffer in the background improves the startup time of the database which becomes significant when the size of the third buffer is very large (e.g., 500 GB+).

Method and system for faster instance startup for large resource configurations

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Mountain View, CA, United States of America

Poojan Kumar