Sap Se

Sybase, Inc.

Ianywhere Solutions, Inc.

Daniel James Farrar

Ivan T Bowman

Robert Schulze

Lars Dannecker

Gordon Gaumnitz

Anisoara Nica

Peter Bumbulis

Daniil Golod

Evguenia A Eflov

Anil Kumar Goel

John Smirnios

Mohammed Abouzour

David Edward DeHaan

Yogi Joshi

Nathan Michael Auch

Paul Tonizzo

Sergiu Pocol

A system and method for faster access for compressed time series data. A set of blocks are generated based on a table stored in a database of the data platform. The table stores data associated with multiple sources of data provided as consecutive values, each block containing index vectors having a range of the consecutive values. A block index is generated for each block having a field start vector representing a starting position of the block relative to the range of consecutive values, and a starting value vector representing a value of the block at the starting position. The field start vector of the block index is accessed to obtain the starting position of a field corresponding to a first block and to the range of the consecutive values of the first block. The starting value vector is then determined from the block index to determine an end and a length of the field of the first block.

Faster access for compressed time series data: the block index

Systems, methods, and computer media are described for index-based join size estimation. For a join operation between two tables, a filter is applied to the first table, resulting in a filter output. The filter output is then sampled. For each sample, an index for a second table is accessed and counts of records in the second table that match the sample are retrieved. Using the sample size and the retrieved counts from the index of the second table, a data size for the join operation can be efficiently and accurately estimated. Statistical confidence in the estimate can also be assessed using variance-based calculations.

Index-based, adaptive join size estimation

Disclosed is a system and method for improving database memory consumption and performance using compression of time stamp columns. A number of time stamps of a time series is received. The time stamps have a start time, and are separated by an equal increment of time that defines an interval. The start time and interval are stored in a dictionary of a column store of a database. An index is generated in the column store of the database, the index having a number of index vectors. Using the index vectors, each time stamp of the number of time stamps can be calculated from the start time stored in the dictionary and the position in the time series based on the interval stored in the dictionary.

Compressing time stamp columns

An operator tree is formed for a data processing plan, the operator tree containing a plurality of interconnected nodes and including a grouping of two or more duplicative portions, each of the two or more duplicative portions having identical nodes and structure such that when the operator tree is executed, operators executed in a first duplicative portion using a first thread perform same functions use different data than operators in a second duplicative portion using a second thread. One or more operators in the first portion and one or more operators in the second portion to be synchronized with each other are identified. A synchronization point is created for the identified operators in the first thread and one or more subsequent threads, wherein the synchronization point receives information from each of the identified operators to build an artifact to deliver to one or more operators that depend on the artifact.

Safe synchronization of parallel data operator trees

Time stamps for time series data can be efficiently compressed by grouping rows in a database table such that time stamp values of the rows in the group are ordered and characterizable by an increment and an offset, which can be stored for the set of rows respectively in an increment column and an offset column such that the time stamp values of the set of rows are represented by a single slope and offset. A run-length compression can be applied to the increment column and offset column for the table.

Formula-encoded time stamps for time series data

A method and system for transforming a serial schedule of transactions into a parallel schedule of transaction is disclosed. In one example, a computer system stores a list of data transactions in a transaction log. The computer system then reads a respective data transaction from the transaction log. The computer system determines whether the respective data transaction is dependent on any other currently pending data transaction. In accordance with a determination that the respective data transaction is not dependent on any other currently pending data transaction, the computer system applies the data changes to a reconstructed data set. In accordance with a determination that the respective data transaction is dependent on a currently pending second data transaction, the computer system delays commitment of the respective data transaction until the second data transaction has been applied to the reconstructed data set.

Converting a serial transaction schedule to a parallel transaction schedule

A flexible, extensible and efficient compile-time mechanism that leverages native high-level application programming language constructs (e.g., the template and macro features of C++), thus minimizing any programmer or a software developer learning curve and eliminating the need for programming tool (e.g., compiler) changes, to identify and control aspects of shared resource access in concurrent software at the time of source code compilation.

System and method for stability guarantees in concurrent software

Systems, methods and computer program products for compression of database indexes are described herein. A system embodiment includes a sequence determiner to scan a database index and to determine a start of a range and end of a range of consistently changing values in one or more index pages of said database index and an index updater to update said database index based on a sequence determined by said sequence determiner, while suspending writing of one or more values that lie within start of said range and end of said range of values. A method embodiment includes scanning an index, determining a pattern of changing values in one or more index pages of said index and selectively updating said index based on said determining step to minimize index insertions. The method embodiment further includes determining a start of a range of values and an end of said range of values in an index page, setting appropriate bits to identify said start of range of values and end of range of values, determining if an entry to be inserted can appended to at the end of said range of values, and compressing said index by suspending writing of one or more values that occur between said start of range of values and said end of range of values.

Index compression in databases

Systems, methods and computer program products for detecting potential architecture and interfacing issues in database applications are described herein. In an embodiment, the invention operates by accessing trace information. The trace information includes database-related information pertaining to interactions of a database application with a production database. The invention detects potential architecture and interfacing issues in the database application by analyzing the trace information. Such architecture and interfacing issues include, but are not limited to, multiple connections simultaneously blocking on the same row of a table, and client-side joins.

Detecting performance degrading design and algorithm issues in database applications

A database system with methodology for automated determination and selection of optimal indexes is described. In one embodiment, for example, in a database system, a method of the present invention is described for recommending database indexes to be created for optimizing system performance, the method comprises steps of: capturing a workload representative of database queries employed during system use; creating virtual indexes for optimizing system performance during execution of the database queries captured in the workload; computing cost benefits for different combinations of the virtual indexes; and recommending physical indexes to be created based on virtual indexes that have favorable cost benefits for the captured workload.

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Kitchener, Canada

Daniel James Farrar