Oracle International Corporation

Oracel International Corporation

Sujatha Muthulingam

Amit Ganesh

Wei Zhang

Vineet Marwah

Niloy Mukherjee

Tirthankar Lahiri

Gary C Ngai

Teck Hua Lee

Vishwanath Karra

Jonathan D Klein

Dheeraj Pandey

Alex Tsukerman

Krishna Kunchithapadam

Yu Chieh Fu

Benoit Dageville

Juan R Loaiza

Andrew Witkowski

Shasank Kisan Chavan

Karl Dias

Mohamed Ziauddin

Jesse Kamp

Mark Charles Ramacher

Allison Holloway

Vasudha Krishnaswamy

Sanket Hase

Gianfranco Putzolu

Graham Wood

Alexander Tsukerman

Michael J Gleeson

Leng Leng Tan

Kam Shergill

Atrayee Mullick

Bharat Chandra Baddepudi

Vipin Gokhale

Nicholas A Whyte

Sushil Kumar

Wanli Yang

You Jung Kim

Richard Sarwal

Francisco Sanchez

Bharath Aleti

Hsiao-te Su

Kaan Baloglu

Nirman Kumar

Dheerai Pandey

Fan Wu

Vicente Hernandez Jimenez

Sooyeon Jo

Jesus Elohim Martinez Castillo

Techniques are provided for optimizing storage of database records in segments using sub-segments. A base segment is a container used for storing records that belong to a database object. A database management system receives a request to load, into the database object, a first set of records that are in a first state. In response to receiving the request, the system generates a new sub-segment, which is a container that is separate from the base segment. The system stores the first set of records, in their first state, within the sub-segment. The system then monitors one or more characteristics of the database system. In response to the one or more characteristics satisfying criteria, the system performs a migration of one or more records of the first set of records from the sub-segment to the base segment. During the migration, the system converts the one or more records from the first state to a second state and stores the one or more records, in their second state, in the base segment.

Automatic, online and space efficient clustering and compression of very large database objects

A method, apparatus, and system for tracking row and object database activity into block level heatmaps is provided. Database activity including reads, writes, and creates can be tracked by a database management system at the finest possible level of granularity, or the row and object level. To efficiently record the tracked database activity, a two-part structure is described for writing the activity into heatmaps. A hierarchical in-memory component may use a dynamically allocated sparse pool of bitmap blocks. Periodically, the in-memory component is persisted to a stored representation component, sharable with multiple database instances, which may include consolidated last access times and/or a history of heatmap snapshots to reflect access over time. The heatmaps may then be externalized to database users and applications to provide and support a variety of features.

Tracking row and object database activity into block level heatmaps

Techniques are provided for optimizing storage of database data records in segments using sub-segments. A segment may be comprised of a plurality of extents that contain data blocks and a plurality of references to sub-segments. Sub-segments are containers that contain other extents. A request to insert a set of records into a segment may be received by a database management system. Upon receiving the request, a particular sub-segment is selected to temporarily store the set of records. The set of records are inserted into data blocks belonging to an extent of the sub-segment. Access frequency for the set of records is monitored to determine whether the access frequency is less than a first threshold. When the access frequency of a subset of records is less than a first threshold, the subset of records is compressed and inserted into a particular extent of a particular segment.

Self-optimizing database objects using virtual segments

Described are improved systems, computer program products, and methods for obtaining space usage information within a clustered database system. Some approaches provide an improved algorithm and structure that gives the ability to compute the latest and accurate space usage with only in-memory operations.

Efficient space usage cache on a database cluster

To prioritize repopulation of in-memory compression units (IMCU), a database server compresses, into an IMCU, a plurality of data units from a database table. In response to changes to any of the plurality of data units within the database table, the database server performs the steps of: (a) invalidating corresponding data units in the IMCU; (b) incrementing an invalidity counter of the IMCU that reflects how many data units within the IMCU have been invalidated; (c) receiving a data request that targets one or more of the plurality of data units of the database table; (d) in response to receiving the data request, incrementing an access counter of the IMCU; and (e) determining a priority for repopulating the IMCU based, at least in part, on the invalidity counter and the access counter.

Prioritizing repopulation of in-memory compression units

A method, non-transitory computer readable media, and system for hierarchical organization of tablespace free space metadata in a database are provided. The hierarchy is divided into at least two levels: levelor Lblocks are stored as a shared data structure and map free space in a tablespace, whereas levelor Lblocks are stored as separate local copies at each database instance and map to the Lbitmap blocks. The Lblocks each indicate, for each Lblock of a respective subset of a plurality of Lblocks, a maximum size of a largest extent that can be allocated.

Hierarchical tablespace space management

A method, apparatus, and system for a multi-instance database scan server is provided to process data scan operations for segments within in-memory stores, such as in-memory columnar (IMC) stores. The scan server uses a client/server based model, wherein each database instance in the database management system ('DBMS') is associated with a client-side scan server and a server-side scan server. The client-side scan server can reside in the data and/or index layer of the DBMS, receiving requests for scan operations on in-memory segments. After receiving a data scan request from an IMC client, the client-side scan server can create several independently executable scanning tasks to process the request. The scanning tasks are each assigned to a particular server-side scan server for processing based on one or more factors, which may include a load balancing component. Additional factors to be considered may include instance affinity and/or NUMA (Non-Uniform Memory Access) affinity.

Scan server for dual-format database

A method, apparatus, and system for hierarchical organization of tablespace free space metadata in a database are provided. The hierarchy is divided into at least two levels: levelor Lbitmap blocks are stored as a shared data structure and map free space in a tablespace, whereas levelor Lbitmap blocks are stored as separate local copies at each database instance and map to the Lbitmap blocks. This hierarchical organization provides a mechanism for finer grained concurrency control, enabling highly parallel tablespace metadata processing to accommodate the performance requirements of large tablespaces with big data sets. By integrating the hierarchical organization as part of the tablespace stack layer in a database management system (DBMS), implementations can be provided transparently to database end users without demanding any additional administrative, maintenance, or development burdens.

Disclosed are methods, systems, and computer program products for processing a file which include using a computer system that is programmed for performing a process of receiving the file in response to a request for storing the file, determining whether a database already contains the file, and storing the file in the database if the database does not already contain the file. The process may alternatively include receiving the file in response to a request for storing the file, determining whether a database already contains the file, and storing the file without storing the received file if the database already contains the file. The process may also alternatively include receiving the file in response to a request for storing the file in a database, separating the file into a plurality of portions, and storing the plurality of portions so each of the plurality of portions can be individually accessed.

System and method for data de-duplication

A method, system and computer program product are described for state maintenance of a large object. In one approach, the method, system and computer program product perform by associating one or more buffers with a transaction involving a large object, the large object data may be accessed using the one or more buffers during the transaction, and storing data for the large object from the one or more buffers in one or more sets of contiguous blocks. In one approach, a system performs state maintenance of a large object with a cache that associates one or more buffers with a transaction involving a large object, the large object data may be accessed using the one or more buffers during the transaction, and the cache stores large object data from the one or more buffers in one or more sets of contiguous blocks in storage.

Method and system for state maintenance of a large object

Disclosed is a system and method for implementing space management for large objects stored in the computing system. According to some approaches, storage of large objects are managed by dynamically creating contiguous chunks of storage space of varying lengths. The length of each chunk may vary depending upon object size being stored, fragmentation of the storage space, available free space, and/or expected length of the object.

Method and mechanism for implementing dynamic space management for large objects

A method and apparatus for proactively allocating space to a logical layer of a database is provided. Allocation of space to a logical layer of a database is an expensive operation that should be minimized. The allocation of space includes discovering free space in all the higher layers in the logical storage hierarchy. It also includes cross-domain system calls and cleansing disk-write operations. In prior approaches, the allocation processes were triggered on-demand, only a certain logical layer was discovered to be at full capacity when an insert-row operation was attempted. In one embodiment of the invention, space needs are statistically predicted based on prior rates of space consumption. The database server pre-allocates space as needed, based on the statistical predictions. Rates of consumption are examined periodically. Space is pre-allocated before any logical layer reaches full capacity by a combination of proactive background processes; foreground-triggered, background processes; and classic foreground allocation.

Proactive space allocation in a database system

A framework for in-memory space management for content management database systems is provided. A per-instance in-memory dispenser is partitioned. An incoming transaction takes a latch on a partition and obtains sufficient block usage to perform and complete the transaction. Generating redo information is decoupled from transaction level processing and, instead, is performed when block requests are loaded into the in-memory dispenser or synced therefrom to a per-instance on-disk structure.

In-memory space management for database systems

Growing community of inventors

Sunnyvale, CA, United States of America

Sujatha Muthulingam