Patents by Inventor Jan Vondrak

Jan Vondrak has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Split elimination in mapreduce systems
    Patent number: 10691646
    Abstract: Embodiments of the present invention relate to elimination of blocks such as splits in distributed processing systems such as MapReduce systems using the Hadoop Distributed Filing System (HDFS). In one embodiment, a method of and computer program product for optimizing queries in distributed processing systems are provided. A query is received. The query includes at least one predicate. The query refers to data. The data includes a plurality of records. Each record comprises a plurality of values in a plurality of attributes. Each record is located in at least one of a plurality of blocks of a distributed file system. Each block has a unique identifier. For each block of the distributed file system, at least one value cluster is determined for an attribute of the plurality of attributes. Each value cluster has a range. The predicate of the query is compared with the at least one value cluster of each block.
    Type: Grant
    Filed: March 5, 2018
    Date of Patent: June 23, 2020
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Mohamed Eltabakh, Peter J. Haas, Fatma Ozcan, Mir Hamid Pirahesh, John (Yannis) Sismanis, Jan Vondrak
  • SPLIT ELIMINATION IN MAPREDUCE SYSTEMS
    Publication number: 20180196828
    Abstract: Embodiments of the present invention relate to elimination of blocks such as splits in distributed processing systems such as MapReduce systems using the Hadoop Distributed Filing System (HDFS). In one embodiment, a method of and computer program product for optimizing queries in distributed processing systems are provided. A query is received. The query includes at least one predicate. The query refers to data. The data includes a plurality of records. Each record comprises a plurality of values in a plurality of attributes. Each record is located in at least one of a plurality of blocks of a distributed file system. Each block has a unique identifier. For each block of the distributed file system, at least one value cluster is determined for an attribute of the plurality of attributes. Each value cluster has a range. The predicate of the query is compared with the at least one value cluster of each block.
    Type: Application
    Filed: March 5, 2018
    Publication date: July 12, 2018
    Inventors: Mohamed Eltabakh, Peter J. Haas, Fatma Ozcan, Mir Hamid Pirahesh, John (Yannis) Sismanis, Jan Vondrak
  • Split elimination in MapReduce systems
    Patent number: 9910860
    Abstract: Embodiments of the present invention relate to elimination of blocks such as splits in distributed processing systems such as MapReduce systems using the Hadoop Distributed Filing System (HDFS). In one embodiment, a method of and computer program product for optimizing queries in distributed processing systems are provided. A query is received. The query includes at least one predicate. The query refers to data. The data includes a plurality of records. Each record comprises a plurality of values in a plurality of attributes. Each record is located in at least one of a plurality of blocks of a distributed file system. Each block has a unique identifier. For each block of the distributed file system, at least one value cluster is determined for an attribute of the plurality of attributes. Each value cluster has a range. The predicate of the query is compared with the at least one value cluster of each block.
    Type: Grant
    Filed: February 6, 2014
    Date of Patent: March 6, 2018
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Mohamed Eltabakh, Peter J. Haas, Fatma Ozcan, Mir Hamid Pirahesh, John (Yannis) Sismanis, Jan Vondrak
  • Machine learning customer valuation functions
    Patent number: 9626630
    Abstract: A computing device determines one or more first degree correlations based on valuation information. The computing device determines one or more important variables based on at least a comparison between the absolute value of the one or more first degree correlations to a first threshold value. The computing device determines a valuation function based on at least one or more of the determined one or more important variables.
    Type: Grant
    Filed: April 1, 2014
    Date of Patent: April 18, 2017
    Assignee: International Business Machines Corporation
    Inventors: Vitaly Feldman, Jan Vondrak
  • MACHINE LEARNING CUSTOMER VALUATION FUNCTIONS
    Publication number: 20150278708
    Abstract: A computing device determines one or more first degree correlations based on valuation information. The computing device determines one or more important variables based on at least a comparison between the absolute value of the one or more first degree correlations to a first threshold value. The computing device determines a valuation function based on at least one or more of the determined one or more important variables.
    Type: Application
    Filed: April 1, 2014
    Publication date: October 1, 2015
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Vitaly Feldman, Jan Vondrak
  • SPLIT ELIMINATION IN MAPREDUCE SYSTEMS
    Publication number: 20150220529
    Abstract: Embodiments of the present invention relate to elimination of blocks such as splits in distributed processing systems such as MapReduce systems using the Hadoop Distributed Filing System (HDFS). In one embodiment, a method of and computer program product for optimizing queries in distributed processing systems are provided. A query is received. The query includes at least one predicate. The query refers to data. The data includes a plurality of records. Each record comprises a plurality of values in a plurality of attributes. Each record is located in at least one of a plurality of blocks of a distributed file system. Each block has a unique identifier. For each block of the distributed file system, at least one value cluster is determined for an attribute of the plurality of attributes. Each value cluster has a range. The predicate of the query is compared with the at least one value cluster of each block.
    Type: Application
    Filed: February 6, 2014
    Publication date: August 6, 2015
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Mohamed Eltabakh, Peter J. Haas, Fatma Ozcan, Mir Hamid Pirahesh, John (Yannis) Sismanis, Jan Vondrak