Sap Se

Sybase, Inc.

Ianywhere Solutions, Inc.

Anil Kumar Goel

Mihnea Andrei

Peter Bumbulis

Colin Florendo

Rolando Blanco

Jeffrey Pound

Nathan Auch

Ivan Schreter

Muhammed Sharique

Anisoara Nica

Scott MacLean

Juchang Lee

Reza Sherkat

John Smirnios

Stefan A Baeuerle

Thomas Legler

Guenter Radestock

Steven A Kirk

Donald Kossmann

Ivan T Bowman

David Wein

Carsten Thiel

Martin Kaufmann

David Edward DeHaan

Ramesh Gupta

Daniil Golod

Asif Iqbal Desai

Somnath Ghosh

Chang Ge

Eric Garber

Minhnea Andrei

Mark Delafranier

Norman May

Volker Sauermann

Arne Harren

Chang Gyoo Park

Michael Wintergerst

Steffen Geissinger

Simon Lueders

Alexander Bunte

Jonathan Bregler

Andreas Kellner

Wolfgang Lehner

Le-Huan Stefan Tran

Daniel Kuntze

Michael Schnaubelt

Sunho Lee

Meinolf Block

Vladislav Leonkev

Frank Renkes

Cornelia Kinder

Deok Koo Kim

Ralph Debusmann

Klaus Kopecz

Daniel James Farrar

Roland F McKenney

Christopher Schildt

Mohammed Abouzour

Andreas Thumfart

Evguenia A Eflov

Thomas Bodner

Pedram Ghodsnia

Vivek Kandiyanallur

Ajay Kumar Srivastava

Andre Hildebrandt

Joydeep Das

Mihnea André

Harin Vadodaria

Harshada Chavan

Francis Gropengiesser

Elias Yousefi Amin Abadi

Hua Fan

Andreas Luethi

Matthias Ringwald

Roger Killian-Kehr

Pooya Saadat-Panah

Puspanantha Shanmuganathan

Jeffrey J Plager

Vipul Sharma

Suprio Ray

A request for an entry of a dictionary having multiple dictionary blocks may be received, where the dictionary stores string values associated with corresponding value identifiers (IDs) for dictionary compression. One of the dictionary blocks may be selectively loaded into memory, and the dictionary block that has been loaded into memory may be searched. A value ID directory may be constructed in memory, where the value ID directory includes last value IDs for the dictionary blocks, and each of the last value IDs is mapped to an index of one of the dictionary blocks that includes a string value for that last value ID. A separator directory may also be constructed in memory, where the separator directory includes separators for the dictionary blocks, and each of the separators is mapped to an index of one of the dictionary blocks that includes a string value for that separator.

Paged column dictionary

Partitioning of temporal databases can implement distributed storage of temporal data via time-based or space-based techniques to improve performance of operators on the database. A variety of operators can be supported for the partitioned tables, including temporal aggregation, time travel, and temporal join. The use of checkpoints can greatly increase performance in a variety of scenarios. The described partitioning techniques can be applied in a parallel execution context to great benefit. The partitioning can also reduce local memory footprint, facilitating in-memory database processing.

Timeline index for partitioned temporal database tables

A transaction management service layer monitors a plurality of read and write transactions being executed by the data engines by way of client libraries at each of a plurality of data engines. In addition, the transaction management server layer maintains and coordinates transaction timestamp and sequence numbers that are shared by the plurality of data engines. The transaction management service layer identifies and resolves conflicts among the plurality of transactions. The transaction management service layer is a separate and independent service that is isolated from other components of the plurality of data engines. Related apparatus, systems, techniques and articles are also described.

Global database transaction management service

A system, computer-implemented method, and a computer-readable storage medium for determining estimations to statistical questions. Data statistics used in evaluating estimations to statistical questions are gathered from multiple sources in a database management system. A statistical question comprising, for example, cardinality estimations is received, wherein the question is posed by different database components, such as query optimizer, or execution engine. Estimation for the statistical question is computed, where the estimation is based on multiple data statistics and without using the data referred to in the question.

Data statistics in data management systems

Cracking page-loadable columns for in-memory data management is described herein. An embodiment operates by accessing a column according to a received query, determining that the received query requires a non-critical data structure associated with the column, and rebuilding the non-critical data structure from data associated with the column.

Cracking page-loadable columns for in-memory data management

A system includes reception of a first write request from a client including a first key and a first one or more stream, payload pairs associated with the first key, copying of the first key and the first one or more stream, payload pairs to a first buffer of a volatile memory, storage of data of the first buffer in one or more blocks of a raw block non-volatile memory device, providing of the first buffer to a stream store server, reception of the first buffer at the stream store server, adding of the first key and the first one or more stream, payload pairs to a second buffer of the volatile memory, in key-order, storage of the data of the second buffer in a filesystem storage device, according to stream, and transmission of an indication of the durability of the key to the tail store server.

Storage of log-structured data

Disclosed herein are system, method, and computer program product embodiments for quorum-based replication of data records. In one embodiment, a read request for reading a record is received from a user node on a replica node of a cluster of replica nodes. The record is then determined not committed on the replica node. In response to the determination, an update message indicative of whether the number of replica nodes on which the record is durable exceeds a threshold is received on the replica node. In response to the number of replica nodes exceeds the threshold, a value of the record on the replica node is transmitted to the user node.

Quorum-based replication of data records

A system includes writing of log data in chunks over a first range of heap log sequence positions of a heap log stored in the non-volatile memory system, and writing of a heap anchor marker in a first anchor stream of a transaction log stored in the non-volatile memory system, at a first transaction log sequence position of the transaction log, wherein the first anchor stream is associated with a first stream of the transaction log, and the heap anchor marker identifies the first range of heap log sequence positions of the heap log.

Handling large writes to distributed logs

A method includes a primary storage unit receiving a first write request including a first key and a first value; persisting the first value in a first non-volatile memory in association with the first key; broadcasting the first write request and a first set of globally-durable keys to secondary storage units; receiving, from the secondary storage units, an acknowledgement of the first write request and a first set of locally-durable keys, each of the first sets of locally-durable keys including the first key; the primary storage unit receiving a second write request including a second key and a second value; persisting the second value in the first non-volatile memory in association with the second key; and broadcasting the second write request and a second set of globally-durable keys to the secondary storage units, the second set of locally-durable keys including the first key. A system is also disclosed.

Replication of log-structured data

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

As part of a database system comprising a combination of on-disk storage and in-memory storage, a plurality of records that comprise a table are stored in a plurality of fragments that include at least a delta fragment and a main fragment retained in the on-disk storage. Each fragment has visibility data structures to enable multi-version concurrency control. Each fragment can be compressed using dictionary compression and n-bits compression. The fragments are loaded into main system memory in the in-memory storage from the on-disk storage if they are accessed for read operations or write operations and are not already in memory. A plurality of lockless read and write operations are concurrently performed, while providing snapshot isolation, on the at least one of the plurality of fragments while the at least one of the plurality of fragments is in the main system memory.

In-memory database system providing lockless read and write operations for OLAP and OLTP transactions

A system, a method, and a computer program product for deployment of objects are disclosed. Using a deployment infrastructure of a database system, a deployment container for deployment of at least one object at runtime of an application is generated. The container includes at least one artifact for the object and a container schema indicative of at least one dependency associated with the object. At least one deployment privilege is associated based on the container schema with the artifact for the object. The artifact of the deployment container is deployed based on the associated deployment schema during runtime of the application. The container can be an isolated container and an access privilege to an object can be requested based on a synonym for deployment purposes.

Database level containers

A compression manager may store, within an index vector, a plurality of value identifiers (IDs), each value ID representing a value within a database. A page generator may designate a number of the value IDs as defining a page within the index vector, so that the index vector includes a plurality of pages, each page including the number of value IDs. The page generator may store the index vector in a secondary memory of a main memory database. An iterator may access a requested value ID, and a page loader may load a corresponding page of the index vector that contains the requested value ID into the main memory database.

Main memory database management using page index vectors

A method and system, the system including a plurality of machines each having a processor and a main memory component; a shared distributed storage facility storing a set of data and accessible by the plurality of machines over a communication network; a controller to select, in response to a state of a query execution plan comprising a plurality of executable jobs for the set of data, which one of a set of scheduling algorithms to execute; an execution engine to execute the selected scheduling algorithm to determine, for each job in the plurality of jobs, which server to schedule to execute the respective job; and providing an indication of the scheduling of the servers determined to be schedules for the execution of the jobs.

Distributed resource-aware task scheduling with replicated data placement in parallel database clusters

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

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Waterloo, Canada

Anil Kumar Goel