International Business Machines Corporation

Globalfoundries Inc.

Naresh K Chainani

Kiran Chinta

Liping Zhang

Vijayshankar Raman

Ronald Jason Barber

Ian R Finlay

Sam Sampson Lightstone

Gopi K Attaluri

Guy Maring Lohman

Richard Sefton Sidle

Ippokratis Pandis

Vincent Kulandaisamy

Calisto Paul Zuzarte

Garth Allen Dickie

Thomas Abel Beavin

Timothy Ray Malkemus

David C Kalmuk

Robin Grosman

Shaorong Liu

Yuan Su

James H Cho

Mir Hamid Pirahesh

Raghupathi Keshava Murthy

Sandeep Tata

Sitaram Vemulapalli

Lynette D Adyilamuriyil

Disclosed aspects relate to data arrangement management in a distributed data cluster environment of a shared pool of configurable computing resources. In the distributed data cluster environment, a set of data is monitored for a data redistribution candidate trigger. The data redistribution candidate trigger is detected with respect to the set of data. Based on the data redistribution candidate trigger, the set of data is analyzed with respect to a candidate data redistribution action. Using the candidate data redistribution action, a new data arrangement associated with the set of data is determined. Accordingly, the new data arrangement is established.

Data arrangement management in a distributed data cluster environment of a shared pool of configurable computing resources

According to embodiments of the present invention, a metadata file is transferred from the first system to the second system and a database on the second system is initialized based on the metadata file. An image, including information of the first system to be restored, is transferred from the first system to the second system, and restoration of the information to the second system based on the image is initiated. Prior to completion of the restoration, one or more log files indicating actions performed on the first system relating to the information to be restored is transferred from the first system to the initialized database on the second system. In response to completion of the restoration, the actions of the log files are performed to synchronize the restored data on the second system with the first system.

Accelerated recovery after a data disaster

A computer-implemented method for a partitioned bloom filter merge is provided. A non-limiting example of the computer-implemented method includes partitioning, by a processing device, a bloom filter into N equal size filter partitions. The method further includes distributing, by the processing device, each of the filter partitions to an associated node. The method further includes merging, by the processing device, the filter partitions in each of the associated nodes. The method further includes redistributing, by the processing device, the merged filter partitions to each of the N nodes. The method further includes joining, by the processing device, the merged filter partitions in each of the N nodes to assemble a complete merged bloom filter.

Partitioned bloom filter merge for massively parallel processing clustered data management

Performing a join of first and second database tables for a query includes applying a predicate of the query to the first table as a first predicate and determining how many distinct join key values the first table has that survive the applying of the first predicate, wherein a join key value of the first table that survives the applying of the first predicate is a surviving join key value for a second predicate. A selection includes selecting among applying the second predicate to the second table, probing the second table with the second predicate, and neither applying the second predicate to the second table nor probing the second table with the second predicate, wherein the selecting is responsive to the number of distinct, surviving join key values.

Technology for join processing

Embodiments include a method, system, and computer program product for encoding data while it is being processed as part of a query is provided. The method includes receiving a query request and determining a set of values associated with data to be encoded for completing the query request. The method also includes encoding those values such that any subsequent processing operations can be performed on the encoded values to complete the requested query. After performing the subsequent processing operations to complete the requested query, each value is decoded back to its original value.

On-the-fly encoding method for efficient grouping and aggregation

A method includes joining data between at least two data sets. Values of one or more join attributes of each of the data sets is represented in a compressed form, indicated by an encoding scheme. A compression scheme for the one or more join attributes is dynamically selected.

Efficient join on dynamically compressed inner for improved fit into cache hierarchy

A first query is detected. The first query is for a storage device, and pulls a result set from the storage device using a set of predicates. The first query satisfies a size criterion. A new set of predicates of the result set is identified. The new set of predicates does not include any predicates of the original set of predicates. A second query which is the same as the first query is detected. The new set of predicates is used to determine the result set.

Managing complex queries with predicates

According to one embodiment of the present invention, a system may execute database queries and may comprise a computer system including at least one processor. The system may select a column of a first table as a candidate column for creating a dictionary, create tokens for a foreign key in a second table that corresponds to a primary key in the first table, generate the dictionary for the selected column using the created tokens as indexes in the dictionary and modify a query accessing the column of the first table to retrieve column values based on the dictionary. Embodiments of the present invention further include a method and computer program product executing database queries in substantially the same manner described above.

Query processing using a dimension table implemented as decompression dictionaries

According to one embodiment of the present invention, a method of transferring filters for operations in a distributed system comprises generating at each source node a first filter of a first size. The first filter indicates elements of objects that need not be processed for an operation. Each source node generates one more second filters of a second size less than the first size. Each generated second filter is based on a prior generated filter with each location representing a plurality of locations from the prior generated filter. A second filter is transferred from each source node to each of destination node. The elements of the objects to remove for the operation are determined based on the transferred second filters. Embodiments of the present invention further include a system and computer program product for transferring filters in a distributed system in substantially the same manners described above.

Efficient join-filters for parallel processing

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Portland, OR, United States of America

Naresh K Chainani