Micro Focus Lcc

Jaimin Mukesh Dave

Charles Edward Bear

Benjamin M Vandiver

Hoa Binh Nga Tran

Vivek Bharathan

Styliani Pantela

Pratyush Parimal

Niccolo Meneghetti

Kahlil Bre Oppenheimer

A technique includes performing optimistic concurrency control to process a request associated with a transaction to change a schema of an object. Performing the optimistic concurrency control includes locally modifying the object to change the schema of the object based on the request; after locally modifying the object, locking a global catalog to block the object from being globally modified; validating the locally modified object based on the global catalog; and committing the modified object to a globally shared storage in response to the modified object being validated.

Optimistic concurrency control for database transactions

A technique includes storing, by a computer, a composite metadata object in a catalog. The composite metadata object represents information about a plurality of database objects of a table structure; the table structure includes a plurality of rows and a plurality of columns; the plurality of database objects is associated with a subset of rows of the plurality of rows; and the plurality of database objects is associated with a plurality of files corresponding to the columns. The technique includes processing, by the computer, a database transaction based on the based on composite metadata object.

Composite metadata objects for database systems

Example implementations relate to optimized queries based on unique attributes. For example, a computing device may include a processor. The processor may receive a query and identify at least one unique attribute based on at least one operation specified in the query or based on an attribute property associated with at least one relational table relevant to the query, the attribute property indicating uniqueness. The processor may modify a data structure representing the query, the data structure having nodes each associated with a respective relational table and the data structure modified to specify a subset of the nodes that are associated with the at least one unique attribute. The processor may optimize the query based on the data structure modified to specify the subset.

Optimize query based on unique attribute

A non-transitory machine-readable storage medium stores instructions that upon execution cause a processor to, in response to a receipt of a query, communicate, via a first encrypted channel using a first key, first encrypted data between a plurality of nodes of a distributed database system, the first encrypted data comprising query metadata and a second key; communicate, via a second encrypted channel, second encrypted data between the plurality of nodes of the distributed database system, the second encrypted channel using the second key included in the first encrypted data, the second encrypted data comprising query data; and generate, by the plurality of nodes of the distributed database system, results for the query based on the query data in the second encrypted data.

Encrypted communication channels for distributed database systems

In an example, a top-k function is associated with a top-k projection for a data storage system. Input data to be loaded into the data storage system is divided and ranked according to the top-k function and stored in the top-k projection.

Top-k projection

According to an example, in a method for managing storage of data from an input table, a projection definition that includes an expression to be executed on data contained in a column of the input table may be accessed. The expression on the data contained in the column of the input table may be executed to obtain results data, which may be stored in an expression projection, in which the expression projection includes a column that provides physical storage for the results data. The results data may be stored in the expression projection, segmented, and encoded. In addition, the expression projection may be stored in a node.

Managing storage of data

In an example, an aggregate function is associated with an aggregate projection for a data storage system. Input data to be loaded into the data storage system is aggregated according to the aggregate function and stored in the aggregate projection.

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Cambridge, MA, United States of America

Jaimin Mukesh Dave