際際滷shows by User: ashutoshbapat9 / http://www.slideshare.net/images/logo.gif 際際滷shows by User: ashutoshbapat9 / Thu, 18 Jul 2019 13:17:55 GMT 際際滷Share feed for 際際滷shows by User: ashutoshbapat9 Pitch detection in Tabla accompaniment /slideshow/pitch-detection-in-tabla-accompaniment/156262920 finalstagepresentation-190718131755
The slides for my MTech Thesis final presentation.]]>
The slides for my MTech Thesis final presentation.]]> Thu, 18 Jul 2019 13:17:55 GMT /slideshow/pitch-detection-in-tabla-accompaniment/156262920 ashutoshbapat9@slideshare.net(ashutoshbapat9) Pitch detection in Tabla accompaniment ashutoshbapat9 The slides for my MTech Thesis final presentation. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/finalstagepresentation-190718131755-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The slides for my MTech Thesis final presentation.
Pitch detection in Tabla accompaniment from Ashutosh Bapat
]]> 129 1 https://cdn.slidesharecdn.com/ss_thumbnails/finalstagepresentation-190718131755-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Query optimization techniques for partitioned tables. /slideshow/query-optimization-techniques-for-partitioned-tables/90150971 queryoptimizationparttables-180309125110
Unlike inheritance based partitioning, declarative partitioning introduced in PostgreSQL 10 leaves nothing to infer about how the data is divided into partitions. PostgreSQL 11s query optimizer is gearing up to take advantage of this no-inference representation. While basic partition-wise join has been already committed, patches for various techniques like partition pruning, partition-wise aggregate/grouping and partition-wise ordering are proposed on hackers. Partition-wise join, partition-wise aggregates and partition-wise ordering break a large operation into smaller ones enabling use of smaller hash tables, faster in-memory sorts, per partition indexes, FDW pushdown (in case of foreign partitions) to speed up the large operation. Parallel append technique brings parallel query and partitioning together to improve query performance. We hope that most of those will make it to v11. This talk explains these techniques with performance numbers.]]>
Unlike inheritance based partitioning, declarative partitioning introduced in PostgreSQL 10 leaves nothing to infer about how the data is divided into partitions. PostgreSQL 11s query optimizer is gearing up to take advantage of this no-inference representation. While basic partition-wise join has been already committed, patches for various techniques like partition pruning, partition-wise aggregate/grouping and partition-wise ordering are proposed on hackers. Partition-wise join, partition-wise aggregates and partition-wise ordering break a large operation into smaller ones enabling use of smaller hash tables, faster in-memory sorts, per partition indexes, FDW pushdown (in case of foreign partitions) to speed up the large operation. Parallel append technique brings parallel query and partitioning together to improve query performance. We hope that most of those will make it to v11. This talk explains these techniques with performance numbers.]]> Fri, 09 Mar 2018 12:51:10 GMT /slideshow/query-optimization-techniques-for-partitioned-tables/90150971 ashutoshbapat9@slideshare.net(ashutoshbapat9) Query optimization techniques for partitioned tables. ashutoshbapat9 Unlike inheritance based partitioning, declarative partitioning introduced in PostgreSQL 10 leaves nothing to infer about how the data is divided into partitions. PostgreSQL 11s query optimizer is gearing up to take advantage of this no-inference representation. While basic partition-wise join has been already committed, patches for various techniques like partition pruning, partition-wise aggregate/grouping and partition-wise ordering are proposed on hackers. Partition-wise join, partition-wise aggregates and partition-wise ordering break a large operation into smaller ones enabling use of smaller hash tables, faster in-memory sorts, per partition indexes, FDW pushdown (in case of foreign partitions) to speed up the large operation. Parallel append technique brings parallel query and partitioning together to improve query performance. We hope that most of those will make it to v11. This talk explains these techniques with performance numbers. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/queryoptimizationparttables-180309125110-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Unlike inheritance based partitioning, declarative partitioning introduced in PostgreSQL 10 leaves nothing to infer about how the data is divided into partitions. PostgreSQL 11s query optimizer is gearing up to take advantage of this no-inference representation. While basic partition-wise join has been already committed, patches for various techniques like partition pruning, partition-wise aggregate/grouping and partition-wise ordering are proposed on hackers. Partition-wise join, partition-wise aggregates and partition-wise ordering break a large operation into smaller ones enabling use of smaller hash tables, faster in-memory sorts, per partition indexes, FDW pushdown (in case of foreign partitions) to speed up the large operation. Parallel append technique brings parallel query and partitioning together to improve query performance. We hope that most of those will make it to v11. This talk explains these techniques with performance numbers.
Query optimization techniques for partitioned tables. from Ashutosh Bapat
]]> 727 4 https://cdn.slidesharecdn.com/ss_thumbnails/queryoptimizationparttables-180309125110-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Partition and conquer large data in PostgreSQL 10 /slideshow/partition-and-conquer-large-data-in-postgresql-10/72849010 declpartpgconfindia2017-170306083924
Presentation at PGConf India 2017.]]>
Presentation at PGConf India 2017.]]> Mon, 06 Mar 2017 08:39:24 GMT /slideshow/partition-and-conquer-large-data-in-postgresql-10/72849010 ashutoshbapat9@slideshare.net(ashutoshbapat9) Partition and conquer large data in PostgreSQL 10 ashutoshbapat9 Presentation at PGConf India 2017. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/declpartpgconfindia2017-170306083924-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presentation at PGConf India 2017.
Partition and conquer large data in PostgreSQL 10 from Ashutosh Bapat
]]> 2104 6 https://cdn.slidesharecdn.com/ss_thumbnails/declpartpgconfindia2017-170306083924-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Atomicity for transactions involving foreign server in PostgreSQL /slideshow/atomicit/49734147 atomicforeigntransactions-150623130009-lva1-app6891
際際滷s for my presentation at PGCon 2015 at Ottawa, Canada. The presentation covered the proposed design and implementation of atomicity for transactions involving foreign servers.]]>
際際滷s for my presentation at PGCon 2015 at Ottawa, Canada. The presentation covered the proposed design and implementation of atomicity for transactions involving foreign servers.]]> Tue, 23 Jun 2015 13:00:09 GMT /slideshow/atomicit/49734147 ashutoshbapat9@slideshare.net(ashutoshbapat9) Atomicity for transactions involving foreign server in PostgreSQL ashutoshbapat9 際際滷s for my presentation at PGCon 2015 at Ottawa, Canada. The presentation covered the proposed design and implementation of atomicity for transactions involving foreign servers. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/atomicforeigntransactions-150623130009-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s for my presentation at PGCon 2015 at Ottawa, Canada. The presentation covered the proposed design and implementation of atomicity for transactions involving foreign servers.
Atomicity for transactions involving foreign server in PostgreSQL from Ashutosh Bapat
]]> 864 1 https://cdn.slidesharecdn.com/ss_thumbnails/atomicforeigntransactions-150623130009-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Materialized views in PostgreSQL /slideshow/mv-at-ipug/33397242 mvatipug-140410230928-phpapp02
Presentation introducing materialized views in PostgreSQL with use cases. These slides were used for my talk at Indian PostgreSQL Users Group meetup at Hyderabad on 28th March, 2014]]>
Presentation introducing materialized views in PostgreSQL with use cases. These slides were used for my talk at Indian PostgreSQL Users Group meetup at Hyderabad on 28th March, 2014]]> Thu, 10 Apr 2014 23:09:28 GMT /slideshow/mv-at-ipug/33397242 ashutoshbapat9@slideshare.net(ashutoshbapat9) Materialized views in PostgreSQL ashutoshbapat9 Presentation introducing materialized views in PostgreSQL with use cases. These slides were used for my talk at Indian PostgreSQL Users Group meetup at Hyderabad on 28th March, 2014 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mvatipug-140410230928-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presentation introducing materialized views in PostgreSQL with use cases. These slides were used for my talk at Indian PostgreSQL Users Group meetup at Hyderabad on 28th March, 2014
Materialized views in PostgreSQL from Ashutosh Bapat
]]> 5990 5 https://cdn.slidesharecdn.com/ss_thumbnails/mvatipug-140410230928-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Pgxc scalability pg_open2012 /slideshow/pgxc-scalability-pgopen2012/33358828 pgxcscalabilitypgopen2012-140410040036-phpapp02
A presentation on how to scale out using Postgres-XC.]]>
A presentation on how to scale out using Postgres-XC.]]> Thu, 10 Apr 2014 04:00:36 GMT /slideshow/pgxc-scalability-pgopen2012/33358828 ashutoshbapat9@slideshare.net(ashutoshbapat9) Pgxc scalability pg_open2012 ashutoshbapat9 A presentation on how to scale out using Postgres-XC. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/pgxcscalabilitypgopen2012-140410040036-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A presentation on how to scale out using Postgres-XC.
Pgxc scalability pg_open2012 from Ashutosh Bapat
]]> 789 3 https://cdn.slidesharecdn.com/ss_thumbnails/pgxcscalabilitypgopen2012-140410040036-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Introduction to Postrges-XC /slideshow/introduction-to-postrgesxc/33358681 postgres-xcinosi-140410035554-phpapp02
An introductory presentation on Postgres-XC.]]>
An introductory presentation on Postgres-XC.]]> Thu, 10 Apr 2014 03:55:54 GMT /slideshow/introduction-to-postrgesxc/33358681 ashutoshbapat9@slideshare.net(ashutoshbapat9) Introduction to Postrges-XC ashutoshbapat9 An introductory presentation on Postgres-XC. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/postgres-xcinosi-140410035554-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> An introductory presentation on Postgres-XC.
Introduction to Postrges-XC from Ashutosh Bapat
]]> 1228 3 https://cdn.slidesharecdn.com/ss_thumbnails/postgres-xcinosi-140410035554-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-ashutoshbapat9-48x48.jpg?cb=1563455631 Long experience in the field of core database server development in the areas like storage, buffer manager, query processing and optimization. Special exposure to distributed database servers. Ability to adapt to the work cultures from world class large organizations like Sybase to start-ups like EnterpriseDB. Good experience in customer interaction at various levels, representing organization at conferences, technical talks and marketing events. https://cdn.slidesharecdn.com/ss_thumbnails/finalstagepresentation-190718131755-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/pitch-detection-in-tabla-accompaniment/156262920 Pitch detection in Tab... https://cdn.slidesharecdn.com/ss_thumbnails/queryoptimizationparttables-180309125110-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/query-optimization-techniques-for-partitioned-tables/90150971 Query optimization tec... https://cdn.slidesharecdn.com/ss_thumbnails/declpartpgconfindia2017-170306083924-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/partition-and-conquer-large-data-in-postgresql-10/72849010 Partition and conquer ...