Sap Se

Sybase, Inc.

Sap Global IP Group

Muhammed Sharique

Mihnea Andrei

Anil Kumar Goel

Rolando Blanco

Ivan T Bowman

Surendra Vishnoi

Minhnea Andrei

Ivan Schreter

Thomas Legler

Guenter Radestock

Anisoara Nica

Steven A Kirk

John Smirnios

Sebastian Seifert

Chaitanya Gottipati

Nandan Marathe

Christian Lemke

Carsten Thiel

Peter Steinemann

Gunes Aluc

Mohammed Abouzour

Bernhard Scheirle

Deepak Shrivastava

Mark Delafranier

Sagar Ranadive

Jeffrey J Plager

Vipul Sharma

Mihnea André

Harshada Chavan

Xi Deng

Systems and methods include determination of a first logical page number of a first database page to be persisted, identification of a first blockmap page associated with the first logical page number, determination, from the first blockmap page, of a block number associated with the first logical page number, determination that the block number is an object key, determination, in response to the determination, that the block number is an object key, determination of a first object key to associate with the first logical page number, and writing of the first database page to the object store using the first object key.

Cloud-native object storage for page-based relational database

A system includes reception of a query comprising a join operation on a first table and a second table and a join condition associated with the join operation, determination of a first table column of the first table and a second table column of the second table associated with the join condition, determination of an inferred predicate of the query, the inferred predicate associated with a first column dictionary of the first table column and a second column dictionary of the second table column, determination of a cost of using the inferred predicate to perform the join operation, determination of a plurality of query execution plans to execute the join operation using the inferred predicate, and determination of a cost of each of the plurality of query execution plans based on the cost of using the inferred predicate to perform the join operation.

Inferred predicates for query optimization

A producer-consumer technique includes creating a pool of consumer threads. Producer threads can enqueue work items on a work queue. Consumer threads from the consumer pool are activated to process work items on the work queue. Only one consumer thread at time is activated from the consumer pool, the remaining consumer threads in the pool waiting for an activation event. When signaled by a producer thread, the activated consumer thread pops all the work items from the work queue for processing. The activate consumer thread then signals another consumer thread in the consumer pool by generating an activation event. When the consumer thread has processed its work items, it places itself in the consumer pool by blocking to wait for an activation event.

Producer-consumer communication using multi-work consumers

A system includes a volatile random access memory storing first header data and a first data block, the first header data including descriptive information and a first pointer to the first data block, and a non-volatile random access memory. The system includes determination of a memory size associated with the first header data and the first data block, allocation of a first memory block of the non-volatile random access memory based on the determined memory size, determination of an address of the non-volatile random access memory associated with the allocated first memory block, and writing of the descriptive information and a binary copy of the first data block at the address of the non-volatile random access memory.

Storage of data structures in non-volatile memory

Systems and methods for integrating the lifecycle of nonvolatile memory blocks with the transactional guarantees of a database are disclosed. One method includes creating a first fragment of a first database column in a volatile memory system, receiving a first pointer to a first block of a second non-volatile memory (NVM) system, the first block associated with the first fragment of the first database column, and populating the first block of the second non-volatile memory system using the first pointer. The method further includes committing the first block of the second non-volatile memory system and associating a first block identifier of the first block of the second non-volatile memory system with the first fragment of the first database column, while blocking creation of a database savepoint, and then unblocking creation of the database savepoint. A block key associated with a first fragment may comprise various identifiers such as block, column, table and partition identifiers. A first fragment may be a main column fragment and comprise a first dictionary such as sorted dictionary, while a second fragment may be a delta column fragment and comprise a second dictionary, which may be a non-sorted dictionary.

Lifecycle management for data in non-volatile memory including blocking creation of a database savepoint and associating non-volatile memory block identifiers with database column fragments

Disclosed herein are system, method, and computer program product embodiments for rollover strategies in an n-bit dictionary compressed column store. An embodiment operates by receiving a new value for addition to a compressed column store. It is determined that a maximum storage capacity for tokens in the compressed column store has been reached for the data dictionary. The compressed column store is converted into a composite store including the existing compressed column store and a newly created flat store. The new value is stored in the flat storage portion of the composite store.

Rollover strategies in a n-bit dictionary compressed column store

Systems, methods and computer program product embodiments for providing table parameterized function (TPF) functionality in a database are disclosed herein. An embodiment includes defining a TPF in a database, wherein the definition of the TPF defines one or more parameters of the TPF, at least one of the parameters being a table parameter. A query is received that operates to call the TPF, wherein the query defines one or more input parameters, the input parameters comprising at least one table input parameter to be used as input for calling the TPF. The query is processed to produce a result, and the result of the query is returned.

Table parameterized functions in database

Disclosed herein are system, method, and computer program product embodiments for bloom filter versioning. A request to add a new value to a first bitmap is received, wherein the first bitmap includes a bit sequence corresponding to a most recently added value. It is determined that the first bitmap has exceeded a threshold. A second bitmap is generated, the second bitmap including more bits than the first bitmap. The first bitmap is deleted based upon a determination that a number of readers accessing the first bitmap is zero.

Versioned bloom filter

Disclosed herein are system, method, and computer program product embodiments for exporting and importing database tables in a database management system using multi-version concurrency control (MVCC). An embodiment operates by first initiating an export of a database table in the database management system. During the export transaction, temporary creation and deletion timestamps are identified from MVCC information associated with each row in the database table. Each temporary timestamp is associated with a database transaction. A timestamp map is then generated that associates the identified temporary timestamps with commit timestamps of the associated transactions. The database table, associated MVCC information, timestamp map, and snapshot timestamp of the export transaction are written to a binary file. When an import of the database table is initiated in a database management system, the database table is reconstructed from the table rows, associated MVCC information, timestamp map, and snapshot timestamp of the export transaction in the binary file.

Exporting and importing database tables in a multi-user database environment

Disclosed herein are system, method, and computer program product embodiments for rollover strategies in an n-bit dictionary compressed column store. An embodiment operates by receiving a new value for addition to a compressed column store, determining that a current memory block of a most recently added token to the compressed column store is the insertion block. It is determined that the maximum token value has been reached for the current memory block. A new virtual memory block is created using the current insertion block, and a token corresponding to the new value is stored in the new virtual memory block. In another embodiment, when it is determined a maximum number of token values that may be stored in a compressed column store has been reached for a data dictionary, the compressed column store is converted into a composite store include a flat store where the new value is stored.

Rollover strategies in a N-bit dictionary compressed column store

The current subject matter describes static partitioning and sub-partitioning of a row identifier space associated with a table in a delta memory store of a database so as to allow data to be concurrently inserted into rows identified by the corresponding sub-partitions. A server system associated with the database can receive data to be inserted into a database. The server system can select a sub-fragment of a row identifier space identifying identifiers of rows stored in the database for the table. The sub-fragment can be selected based on a preference specified by an insert operation used for insertion of the data into the columnar database and on availability of the sub-fragment. The server system can insert the data in rows identified by the selected sub-fragment while other data is being concurrently inserted in rows identified by other one or more sub-fragments of the row identifier space.

Static row identifier space partitioning for concurrent data insertion in delta memory store

Disclosed herein are system, method, and computer program product embodiments for populating a hash index and returning a handle to the hash index. An embodiment operates by determining, by at least one processor, during query optimization that a first database query has a query execution plan comprising a sub-query which executes N times a correlated predicate having an operator being one of equal and not equal to a base column. A cost of creating and probing the hash index N times and a cost of fully scanning the base column N times are compared based on the correlated predicate. Based on the comparing, it is determined whether to create on-demand a hash index.

Growing community of inventors

Pune, India

Muhammed Sharique