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Vineet Marwah Phones & Addresses

  • Pleasanton, CA
  • San Ramon, CA
  • Redwood City, CA

Resumes

Resumes

Vineet Marwah Photo 1

Pleasanton, California

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Location:
San Francisco, CA
Industry:
Computer Software
Work:
Nutanix
Engineering

Oracle Apr 2011 - Mar 2017
Senior Director of Development

Oracle Apr 2001 - Mar 2011
Consulting Member of Technical Staff

Sun Microsystems Jun 2000 - Sep 2000
Software Engineer Intern

Niit Limited Aug 1998 - Oct 1999
Senior Software Engineer
Education:
Stanford University 1999 - 2001
Master of Science, Masters, Computer Science
Manipal Academy of Higher Education 1994 - 1998
Bachelor of Engineering, Bachelors, Computer Science, Engineering
Skills:
Databases
Oracle
Software Development
Unix
Distributed Systems
Scalability
Pl/Sql
Linux
Software Engineering
Database Systems
Computer Science
Storage
Java
Data Warehousing
Algorithms
Solaris
Access
Soa
Cloud Computing
Vineet Marwah Photo 2

Vineet Marwah

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Location:
San Francisco, CA
Industry:
Computer Software
Vineet Marwah Photo 3

Vineet Marwah

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Location:
San Francisco Bay Area
Industry:
Computer Software

Business Records

Name / Title
Company / Classification
Phones & Addresses
Vineet Marwah
Radix Consulting, LLC
Consulting Services · Healthcare Consulting
7243 Brower Way, San Ramon, CA 94582

Publications

Us Patents

Techniques For Compression And Processing Optimizations By Using Data Transformations

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US Patent:
8239421, Aug 7, 2012
Filed:
Aug 30, 2010
Appl. No.:
12/871862
Inventors:
Vineet Marwah - San Ramon CA, US
Vikram Kapoor - Cupertino CA, US
Jesse Kamp - Castro Valley CA, US
Kam Shergill - Maidenhead, GB
Roger MacNicol - Hummelstown PA, US
Manosiz Bhattacharyya - San Jose CA, US
Amit Ganesh - San Jose CA, US
Assignee:
Oracle International Corporation - Redwood Shores CA
International Classification:
G06F 17/20
US Classification:
707802, 707809, 707756, 382245, 382248
Abstract:
Described herein are compression and processing optimizations by using data transformation techniques. In example embodiments, a byte-wise differential transformation is applied to columnar data represented as a list of length-value pairs to determine a list of delta pairs that is subsequently compressed and stored on persistent storage. A length separation transformation is applied to separate a list of length-value pairs into a length array and a corresponding data value array, where these two arrays are subsequently compressed and stored separately on persistent storage. A native number transformation is applied to a set of number values to remove the lengths stored in the number values, where the transformed set is stored on persistent storage instead of the original set of number values. A native datetime-type transformation is applied to a set of datetime values to generate an encoding that is used to encode the set of datetime values into an encoded set that is stored on persistent storage instead of the original set.

Compression Analyzer

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US Patent:
8356060, Jan 15, 2013
Filed:
Apr 28, 2010
Appl. No.:
12/769508
Inventors:
Vineet Marwah - San Ramon CA, US
Vikram Kapoor - Cupertino CA, US
Amit Ganesh - San Jose CA, US
Jesse Kamp - San Leandro CA, US
Sachin Kulkarni - Foster City CA, US
Roger Macnicol - Hummelstown PA, US
Kam Shergill - Berkshire, GB
Manosiz Bhattacharyya - San Jose CA, US
Assignee:
Oracle International Corporation - Redwood Shores CA
International Classification:
G06F 7/00
US Classification:
707812, 707693, 707802, 711100, 711170, 382243
Abstract:
Techniques are described herein for automatically selecting the compression techniques to be used on tabular data. A compression analyzer gives users high-level control over the selection process without requiring the user to know details about the specific compression techniques that are available to the compression analyzer. Users are able to specify, for a given set of data, a “balance point” along the spectrum between “maximum performance” and “maximum compression”. The point thus selected is used by the compression analyzer in a variety of ways. For example, in one embodiment, the compression analyzer uses the user-specified balance point to determine which of the available compression techniques qualify as “candidate techniques” for the given set of data. The compression analyzer selects the compression technique to use on a set of data by actually testing the candidate compression techniques against samples from the set of data. After testing the candidate compression techniques against the samples, the resulting compression ratios are compared.

On-Line Transaction Processing (Oltp) Compression And Re-Compression Of Database Data

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US Patent:
8392382, Mar 5, 2013
Filed:
Oct 19, 2007
Appl. No.:
11/875642
Inventors:
Vineet Marwah - San Ramon CA, US
Valentin G. Stredie - Foster City CA, US
Dheeraj Pandey - San Ramon CA, US
Amit Ganesh - San Jose CA, US
Assignee:
Oracle International Corporation - Redwood Shores CA
International Classification:
G06F 7/00
G06F 17/00
US Classification:
707693, 707607
Abstract:
A computer is programmed to compress data of a database in response to database modification language (DML) statements generated by on-line transaction processing (OLTP) systems. In several embodiments, data that is initially added to a database block is left uncompressed until a predetermined condition is satisfied, which happens infrequently (relative to OLTP transactions on the block). When satisfied, the computer automatically compresses all uncompressed data in the block, which increases the amount of unused space in the block. New data is thereafter added uncompressed to the partially compressed block, until satisfaction of a predetermined condition whereby the partially compressed block is again compressed, i. e. re-compressed. Adding of new data to a partially compressed block and its compression are repeated unless another predetermined condition is met, in response to which the block is not further re-compressed, thereby to recognize a limit on the benefit from compression.

Ddl And Dml Support For Hybrid Columnar Compressed Tables

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US Patent:
8521784, Aug 27, 2013
Filed:
Aug 30, 2010
Appl. No.:
12/871882
Inventors:
Amit Ganesh - San Jose CA, US
Vikram Kapoor - Cupertino CA, US
Vineet Marwah - San Ramon CA, US
Kam Shergill - Maidenhead, GB
Roger MacNicol - Hummelstown PA, US
Sachin Kulkarni - Sunnyvale CA, US
Jesse Kamp - Castro Valley CA, US
Assignee:
Oracle International Corporation - Redwood Shores CA
International Classification:
G06F 17/30
US Classification:
707796, 707812, 707769, 707693, 711114, 711112
Abstract:
Techniques for storing and manipulating tabular data are provided. According to one embodiment, a user may control whether tabular data is stored in row-level or column-major format. Furthermore, the user may control the level of data compression to achieve an optimal balance between query performance and compression ratios. Tabular data from within the same table may be stored in both column-major and row-major format and compressed at different levels. In addition, tabular data can migrate between column-major format and row-major format in response to various events. For example, in response to a request to update or lock a row stored in column-major format, the row may be migrated and subsequently stored into row-major format. In one embodiment, table partitions are used to enhance data compression techniques. For example, compression tests are performed on a representative table partition, and a compression map is generated and applied to other table partitions.

Techniques For Maintaining Column Vectors Of Relational Data Within Volatile Memory

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US Patent:
8521788, Aug 27, 2013
Filed:
Dec 7, 2012
Appl. No.:
13/708060
Inventors:
Amit Ganesh - San Jose CA, US
Vineet Marwah - San Ramon CA, US
Jesse Kamp - Castro Valley CA, US
Anindya C. Patthak - Fremont CA, US
Shasank K. Chavan - Menlo Park CA, US
Michael J. Gleeson - Saratoga CA, US
Allison L. Holloway - San Carlos CA, US
Manosiz Bhattacharyya - San Jose CA, US
Assignee:
Oracle International Corporation - Redwood Shores CA
International Classification:
G06F 7/00
US Classification:
707802
Abstract:
Techniques are provided for more efficiently using the bandwidth of the I/O path between a CPU and volatile memory during the performance of database operation. Relational data from a relational table is stored in volatile memory as column vectors, where each column vector contains values for a particular column of the table. A binary-comparable format may be used to represent each value within a column vector, regardless of the data type associated with the column. The column vectors may be compressed and/or encoded while in volatile memory, and decompressed/decoded on-the-fly within the CPU. Alternatively, the CPU may be designed to perform operations directly on the compressed and/or encoded column vector data. In addition, techniques are described that enable the CPU to perform vector processing operations on the column vector values.

Techniques For More Efficient Usage Of Memory-To-Cpu Bandwidth

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US Patent:
8572131, Oct 29, 2013
Filed:
Dec 7, 2012
Appl. No.:
13/708054
Inventors:
Amit Ganesh - San Jose CA, US
Vineet Marwah - San Ramon CA, US
Jesse Kamp - Castro Valley CA, US
Anindya C. Patthak - Fremont CA, US
Shasank K. Chavan - Menlo Park CA, US
Michael J. Gleeson - Saratoga CA, US
Allison L. Holloway - San Carlos CA, US
Manosiz Bhattacharyya - San Jose CA, US
Assignee:
Oracle International Corporation - Redwood Shores CA
International Classification:
G06F 12/00
US Classification:
707802, 711100
Abstract:
Techniques are provided for more efficiently using the bandwidth of the I/O path between a CPU and volatile memory during the performance of database operation. Relational data from a relational table is stored in volatile memory as column vectors, where each column vector contains values for a particular column of the table. A binary-comparable format may be used to represent each value within a column vector, regardless of the data type associated with the column. The column vectors may be compressed and/or encoded while in volatile memory, and decompressed/decoded on-the-fly within the CPU. Alternatively, the CPU may be designed to perform operations directly on the compressed and/or encoded column vector data. In addition, techniques are described that enable the CPU to perform vector processing operations on the column vector values.

Ddl And Dml Support For Hybrid Columnar Compressed Tables

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US Patent:
8583692, Nov 12, 2013
Filed:
Aug 30, 2010
Appl. No.:
12/871882
Inventors:
Amit Ganesh - San Jose CA, US
Vikram Kapoor - Cupertino CA, US
Vineet Marwah - San Ramon CA, US
Kam Shergill - Maidenhead, GB
Roger MacNicol - Hummelstown PA, US
Sachin Kulkarni - Sunnyvale CA, US
Jesse Kamp - Castro Valley CA, US
Assignee:
Oracle International Corporation - Redwood Shores CA
International Classification:
G06F 17/30
US Classification:
707796, 707812, 707769, 707693, 711114, 711112
Abstract:
Techniques for storing and manipulating tabular data are provided. According to one embodiment, a user may control whether tabular data is stored in row-level or column-major format. Furthermore, the user may control the level of data compression to achieve an optimal balance between query performance and compression ratios. Tabular data from within the same table may be stored in both column-major and row-major format and compressed at different levels. In addition, tabular data can migrate between column-major format and row-major format in response to various events. For example, in response to a request to update or lock a row stored in column-major format, the row may be migrated and subsequently stored into row-major format. In one embodiment, table partitions are used to enhance data compression techniques. For example, compression tests are performed on a representative table partition, and a compression map is generated and applied to other table partitions.

Storing Compression Units In Relational Tables

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US Patent:
8645337, Feb 4, 2014
Filed:
Apr 28, 2010
Appl. No.:
12/769205
Inventors:
Vikram Kapoor - Cupertino CA, US
Amit Ganesh - San Jose CA, US
Jesse Kamp - San Leandro CA, US
Sachin Kulkarni - Foster City CA, US
Vineet Marwah - San Ramon CA, US
Kam Shergill - Berkshire, GB
Roger Macnicol - Hummelstown PA, US
Manosiz Bhattacharyya - San Jose CA, US
Assignee:
Oracle International Corporation - Redwood Shores CA
International Classification:
G06F 7/00
G06F 17/00
G06F 17/30
US Classification:
707693, 707752
Abstract:
A database server stores compressed units in data blocks of a database. A table (or data from a plurality of rows thereof) is first compressed into a “compression unit” using any of a wide variety of compression techniques. The compression unit is then stored in one or more data block rows across one or more data blocks. As a result, a single data block row may comprise compressed data for a plurality of table rows, as encoded within the compression unit. Storage of compression units in data blocks maintains compatibility with existing data block-based databases, thus allowing the use of compression units in preexisting databases without modification to the underlying format of the database. The compression units may, for example, co-exist with uncompressed tables. Various techniques allow a database server to optimize access to data in the compression unit, so that the compression is virtually transparent to the user.
Vineet M Marwah from Pleasanton, CA, age ~45 Get Report