Innovations for adaptive compression and decompression for dictionaries of a column-store database can reduce the amount of memory used for columns of the database, allowing a system to keep column data in memory for more columns, while delays for access operations remain acceptable. For example, dictionary compression variants use different compression techniques and implementation options. Some dictionary compression variants provide more aggressive compression (reduced memory consumption) but result in slower run-time performance. Other dictionary compression variants provide less aggressive compression (higher memory consumption) but support faster run-time performance. As another example, a compression manager can automatically select a dictionary compression variant for a given column in a column-store database. For different dictionary compression variants, the compression manager predicts run-time performance and compressed dictionary size, given the values of the column, and selects one of the dictionary compression variants.

Adaptive dictionary compression/decompression for column-store databases

Methods and systems for the optimization of available computing resources within a virtual environment are disclosed. An exemplary method comprises determining the sizes of the computing resources available to the virtual machine and determining optimal data structures for the virtual machine based on the sizes of the computing resources. The optimal data structures may include an indexing data structure and a historic data. The method may further comprise allocating a Random Access Memory (RAM) and disk storage to the optimal data structures and configuring the optimal data structures within the RAM and the disk storage. The optimization of data structures involves balancing requirements of the indexing data structure and the historic data.

Optimizing available computing resources within a virtual environment

A system, method, and computer program for compressing packet data is provided. In exemplary embodiments, one or more prefix arrays may be generated for retrieved data, and used as the basis for predicting subsequent data. The packet data may be compressed based, at least partially, on the predicted subsequent data. Accordingly, the compressed packet data may be transferred over a communication network.

Systems and methods for compressing packet data by predicting subsequent data

A system for matching data using flow based packet data storage includes a communications interface and a processor. A communications interface receives a packet between a source and a destination. The processor identifies a flow between the source and the destination based on the packet. The processor determines whether some of packet data of the packet indicates a potential match to data in storage using hashes. The processor then stores the data from the most likely data match and second most likely data match without a packet header in a block of memory in the storage based on the flow.

Data Matching Using Flow Based Packet Data Storage

Disclosed herein are systems and methods for the creation, maintenance and management of virtual overlay networks across multiple communication networks managed by service providers. The simple creation and management of network overlays is accomplished via a network orchestrator manager, allowing for automation of configuration of connected network devices throughout an entire organization's network, regardless of the physical location of each device.

Virtual Network Overlay

Embodiments of the invention relate to a multi-level database compression technique to compress table data objects stored in pages. A compact dictionary structure is encoded that represents frequent values of data at any level of granularity. More than one level of compression is provided, wherein input to a finer level of granularity is an output of a coarser level of granularity. Based upon the encoded dictionary structure, a compression technique is applied to a stored page to compress each row on the page. Similarly, a de-compression technique may be applied to decompress the compressed data, utilizing the same dictionary structures at each level of granularity.

Multi-level database compression

Systems and methods are provided for creating a sandbox for an original tenant at a point in time, the original tenant having original tenant data stored in an immutable storage associated with an original tenant identifier, the original tenant data as of the sandbox creation point in time being a virtual snapshot of the original tenant data accessible by a sandbox tenant, where the sandbox tenant data can be changed without changing the original tenant data, and the original tenant data can be changed without changing the sandbox tenant data. A sandbox tenant is created by associating a sandbox tenant identifier with the virtual snapshot of the original tenant data and with sandbox tenant data created by the sandbox tenant subsequent to the sandbox creation point in time. Original tenant data is subsequently created and associated with the original tenant identifier, and is not accessible to the sandbox tenant.

Formation and manipulation of test data in a database system

Techniques are disclosed relating to maintaining a cache usable to locate data stored in a data structure. A computer system, in various embodiments, maintains a data structure having a plurality of levels that store files for a database. The files may include one or more records that each have a key and corresponding data. The computer system may also maintain a cache for the database whose entries store, for a key, an indication of a location of a corresponding record in a file of the data structure. In some embodiments, the computer system receives a request to access a particular record stored in the data structure where the request specifies a key usable to locate the particular record. The computer system may retrieve, from the cache via the key, a particular indication of a location of the particular record and may use the particular indication to access the particular record.

Cache for efficient record lookups in an LSM data structure

Techniques are disclosed relating to efficiently processing of concurrent database transactions. In one embodiment, a database system receives a first key-value pair for a database transaction and stores the key-value pair in a data structure for active database transactions. The storing may include indexing into a hash table of the data structure with a key of the key-value pair to identify a hash bucket of the hash table corresponding to the key, acquiring a latch associated with the identified hash bucket, and, based on a state of the acquired latch, appending, to the hash bucket, a record specifying the key-value pair. The database system may cause the key-value pair from the data structure to be committed to persistent storage in response to the database transaction being committed.

Database concurrency control through hash-bucket latching

Systems and methods are provided for migrating a tenant of a database system from a source database instance to a destination database instance. The systems and methods include quiescing the tenant data of the tenant to be migrated from the source database instance to the destination database instance so that no new data is written to the storage of the database system associated with the tenant identifier at the source database instance, transmitting metadata of the tenant to be migrated from the source database instance to the destination database instance, and modifying, at the destination database instance, the metadata of the tenant so that the destination database instance has information to point to groupings of data in the storage for the destination database to access the tenant data.

Fanghaenel Thomas

Papers

Multi-level database compression

Formation and manipulation of test data in a database system

Cache for efficient record lookups in an LSM data structure

Database concurrency control through hash-bucket latching

Systems and methods of database tenant migration