SlideShare a Scribd company logo
Sedna XML Database: Query Executor Ivan Shcheklein [email_address] Software Developer  Sedna Team
Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Sedna Architecture
Executor: Architecture Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Executor: Basic Features ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Query Execution Plan ,[object Object],[object Object],fn:count(    for  $x  in  fn:doc( “auction” )//person/name    where  $x  =   “John”    return  $x) continues …
Query Execution Plan ,[object Object],[object Object],fn:doc( “auction” )//person/name “ John” $x $x
Physical Operations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Physical Operations: Basic Interface ,[object Object],class  PPIterator { protected : dynamic_context *cxt;   /// variable bindings context, static context ... public : virtual void  open  ()  = 0; /// initializes state  virtual void  next  (tuple &t)  = 0; /// stores next tuple in t virtual void  close  ()  = 0; /// drops state of the operation virtual void  reopen  ()  = 0; /// fast implementation of close-open …  }; ,[object Object]
Physical Operations: Tuple ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Physical Operations: Extended Interface ,[object Object],[object Object],class  PPVarIterator :  public  PPIterator { public : /// register consumer of the variable dsc virtual  var_c_id register_consumer(var_dsc dsc) = 0; /// get next value of the variable by id virtual void  next(tuple &t, var_dsc dsc, var_c_id id) = 0; … }; ,[object Object],example …
Example fn:doc( “auction” )//person/name “ John” $x fn:count(    for  $x  in  fn:doc( “auction” )//person/name    where  $x  =   “John”    return  $x) $x $x
Two-phase Sorting ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
SQL Connection ,[object Object],[object Object],[object Object],[object Object],[object Object],declare namespace  sql= "http://modis.ispras.ru/Sedna/SQL" ; let  $connection :=  sql:connect ( "odbc:driver://localhost/somedb” ) return sql:execut e($connection,  "SELECT * FROM people WHERE name = ’Peter’" )
Foreign Functions Interface ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],declare function  log($a  as xs:double )  as   xs:double   external ; log(10)
Sedna  Benchmarks ,[object Object],[object Object],[object Object],  Data Size (MB): 50 100  500 XPath 0.5  0.8 3.1 XPath, pos, trans 1.5 1.7 13.3 Complex XPath 1.1 2.2 9.9 Id comparison 1.0 2.3 10. 9 XPath, count 0.2 0.4 1.4 FLWR 0.3 0.5 1.8 FLWR, count 0.4 0.8 3.0 Join(1,2) 263 1046 */154 Join(1,2,3) 340 1350 * Group by 40 81 237 Semijoin 423 1664 */173 Complex semijoin 97 373 * Struct. XPath + trans 0. 9 1.3 6. 1 Contains substring 5. 9 8.4 54.6 Long XPath 0.07 0.1 0.2 Nested Long XPath 0.45 0.7 3.2 Empty 1.9 2.1 1 1 Function Calls 0.5 1.0 6.2 Sorting 1.9 3.5 29.4 Trans(nested XPaths) 0. 5 2.5 4.5
Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Questions ?
Sedna vs. X-Hive ,[object Object],[object Object],[object Object],  X-Hive Sedna XPath 1.2 0.8 XPath, pos, trans 4.0 1.7 Complex XPath 6.8 2.2 Id comparison 3.7 2.3 XPath, count 3.0 0.4 FLWR 4.6 0.5 FLWR, count 16.1 0.8 Join(1,2) * 1046 Join(1,2,3) * 1350 Group by 34.8 81 Semijoin * 1664 Complex semijoin * 373 Struct. XPath + trans 3.3 1.3 Contains substring 10.4 8.4 Long XPath 1.8 0.1 Nested Long XPath 2.3 0.7 Empty 3.1 2.1 Function Calls 2.6 1.0 Sorting 24.3 3.5 Trans(nested XPaths) 3.3 2.5
Sedna vs.  Berkeley XML DB ,[object Object],[object Object],[object Object],  BDB node Sedna  XPath 0.172 0.109 XPath, pos, trans 0.421 0.188 Complex XPath 0.625 0.141 Id comparison 0.969 0.250 XPath, count 0.188 0.094 FLWR 1.297 0.109 FLWR, count 7.016 0.172 Join(1,2) 263.219 11.109 Join(1,2,3) 428.453 14.125 Group by 42.250 2.219 Semijoin 281.781 34.625 Complex semijoin 81.453 10.969 Struct. XPath, trans 0.109 0.454 Contains substring 3.797 2.485 Long XPath 0.219 0.047 Nested Long XPath 0.234 0.156 Empty 0.312 0.125 Function Calls * 0.062 Sorting * 0.43 Trans(nested XPathes) 1.016 0.156

More Related Content

What's hot

Big Data Analytics Lab File
Big Data Analytics Lab FileBig Data Analytics Lab File
Big Data Analytics Lab File
Uttam Singh Chaudhary
 
DataBase Management System Lab File
DataBase Management System Lab FileDataBase Management System Lab File
DataBase Management System Lab File
Uttam Singh Chaudhary
 
1 list datastructures
1 list datastructures1 list datastructures
1 list datastructures
Nguync91368
 
2 a stacks
2 a stacks2 a stacks
2 a stacks
Nguync91368
 
04 data accesstechnologies
04 data accesstechnologies04 data accesstechnologies
04 data accesstechnologies
Bat Programmer
 
The life of a query (oracle edition)
The life of a query (oracle edition)The life of a query (oracle edition)
The life of a query (oracle edition)
maclean liu
 
Rendering XML Document
Rendering XML DocumentRendering XML Document
Rendering XML Document
yht4ever
 
DNS exfiltration using sqlmap
DNS exfiltration using sqlmapDNS exfiltration using sqlmap
DNS exfiltration using sqlmap
Miroslav Stampar
 
Connecting and using PostgreSQL database with psycopg2 [Python 2.7]
Connecting and using PostgreSQL database with psycopg2 [Python 2.7]Connecting and using PostgreSQL database with psycopg2 [Python 2.7]
Connecting and using PostgreSQL database with psycopg2 [Python 2.7]
Dinesh Neupane
 
Java full stack1
Java full stack1Java full stack1
Java full stack1
pravash sahoo
 
Java 1-contd
Java 1-contdJava 1-contd
Java 1-contd
Mukesh Tekwani
 
Apache pig presentation_siddharth_mathur
Apache pig presentation_siddharth_mathurApache pig presentation_siddharth_mathur
Apache pig presentation_siddharth_mathur
Siddharth Mathur
 
Namespace in C++ Programming Language
Namespace in C++ Programming LanguageNamespace in C++ Programming Language
Namespace in C++ Programming Language
Himanshu Choudhary
 
Modular programming Using Object in Scala
Modular programming Using Object in ScalaModular programming Using Object in Scala
Modular programming Using Object in Scala
Knoldus Inc.
 
Python 3.6 Features 20161207
Python 3.6 Features 20161207Python 3.6 Features 20161207
Python 3.6 Features 20161207
Jay Coskey
 
Dynamic memory allocation
Dynamic memory allocationDynamic memory allocation
Dynamic memory allocation
Moniruzzaman _
 
Query hierarchical data the easy way, with CTEs
Query hierarchical data the easy way, with CTEsQuery hierarchical data the easy way, with CTEs
Query hierarchical data the easy way, with CTEs
MariaDB plc
 
XML SAX PARSING
XML SAX PARSING XML SAX PARSING
XML SAX PARSING
Eviatar Levy
 
data loading and unloading in IBM Netezza by www.etraining.guru
data loading and unloading in IBM Netezza by www.etraining.gurudata loading and unloading in IBM Netezza by www.etraining.guru
data loading and unloading in IBM Netezza by www.etraining.guru
Ravikumar Nandigam
 
Apache Flink Training: DataStream API Part 2 Advanced
Apache Flink Training: DataStream API Part 2 Advanced Apache Flink Training: DataStream API Part 2 Advanced
Apache Flink Training: DataStream API Part 2 Advanced
Flink Forward
 

What's hot (20)

Big Data Analytics Lab File
Big Data Analytics Lab FileBig Data Analytics Lab File
Big Data Analytics Lab File
 
DataBase Management System Lab File
DataBase Management System Lab FileDataBase Management System Lab File
DataBase Management System Lab File
 
1 list datastructures
1 list datastructures1 list datastructures
1 list datastructures
 
2 a stacks
2 a stacks2 a stacks
2 a stacks
 
04 data accesstechnologies
04 data accesstechnologies04 data accesstechnologies
04 data accesstechnologies
 
The life of a query (oracle edition)
The life of a query (oracle edition)The life of a query (oracle edition)
The life of a query (oracle edition)
 
Rendering XML Document
Rendering XML DocumentRendering XML Document
Rendering XML Document
 
DNS exfiltration using sqlmap
DNS exfiltration using sqlmapDNS exfiltration using sqlmap
DNS exfiltration using sqlmap
 
Connecting and using PostgreSQL database with psycopg2 [Python 2.7]
Connecting and using PostgreSQL database with psycopg2 [Python 2.7]Connecting and using PostgreSQL database with psycopg2 [Python 2.7]
Connecting and using PostgreSQL database with psycopg2 [Python 2.7]
 
Java full stack1
Java full stack1Java full stack1
Java full stack1
 
Java 1-contd
Java 1-contdJava 1-contd
Java 1-contd
 
Apache pig presentation_siddharth_mathur
Apache pig presentation_siddharth_mathurApache pig presentation_siddharth_mathur
Apache pig presentation_siddharth_mathur
 
Namespace in C++ Programming Language
Namespace in C++ Programming LanguageNamespace in C++ Programming Language
Namespace in C++ Programming Language
 
Modular programming Using Object in Scala
Modular programming Using Object in ScalaModular programming Using Object in Scala
Modular programming Using Object in Scala
 
Python 3.6 Features 20161207
Python 3.6 Features 20161207Python 3.6 Features 20161207
Python 3.6 Features 20161207
 
Dynamic memory allocation
Dynamic memory allocationDynamic memory allocation
Dynamic memory allocation
 
Query hierarchical data the easy way, with CTEs
Query hierarchical data the easy way, with CTEsQuery hierarchical data the easy way, with CTEs
Query hierarchical data the easy way, with CTEs
 
XML SAX PARSING
XML SAX PARSING XML SAX PARSING
XML SAX PARSING
 
data loading and unloading in IBM Netezza by www.etraining.guru
data loading and unloading in IBM Netezza by www.etraining.gurudata loading and unloading in IBM Netezza by www.etraining.guru
data loading and unloading in IBM Netezza by www.etraining.guru
 
Apache Flink Training: DataStream API Part 2 Advanced
Apache Flink Training: DataStream API Part 2 Advanced Apache Flink Training: DataStream API Part 2 Advanced
Apache Flink Training: DataStream API Part 2 Advanced
 

Similar to Sedna XML Database: Executor Internals

Leveraging Azure Databricks to minimize time to insight by combining Batch an...
Leveraging Azure Databricks to minimize time to insight by combining Batch an...Leveraging Azure Databricks to minimize time to insight by combining Batch an...
Leveraging Azure Databricks to minimize time to insight by combining Batch an...
Microsoft Tech Community
 
Flink internals web
Flink internals web Flink internals web
Flink internals web
Kostas Tzoumas
 
Data-and-Compute-Intensive processing Use Case: Lucene Domain Index
Data-and-Compute-Intensive processing Use Case: Lucene Domain IndexData-and-Compute-Intensive processing Use Case: Lucene Domain Index
Data-and-Compute-Intensive processing Use Case: Lucene Domain Index
Marcelo Ochoa
 
Deep Learning and TensorFlow
Deep Learning and TensorFlowDeep Learning and TensorFlow
Deep Learning and TensorFlow
Oswald Campesato
 
Kerberizing spark. Spark Summit east
Kerberizing spark. Spark Summit eastKerberizing spark. Spark Summit east
Kerberizing spark. Spark Summit east
Jorge Lopez-Malla
 
Apache Spark Workshop, Apr. 2016, Euangelos Linardos
Apache Spark Workshop, Apr. 2016, Euangelos LinardosApache Spark Workshop, Apr. 2016, Euangelos Linardos
Apache Spark Workshop, Apr. 2016, Euangelos Linardos
Euangelos Linardos
 
Accelerated data access
Accelerated data accessAccelerated data access
Accelerated data access
gordonyorke
 
The post release technologies of Crysis 3 (Slides Only) - Stewart Needham
The post release technologies of Crysis 3 (Slides Only) - Stewart NeedhamThe post release technologies of Crysis 3 (Slides Only) - Stewart Needham
The post release technologies of Crysis 3 (Slides Only) - Stewart Needham
Stewart Needham
 
Project Tungsten Phase II: Joining a Billion Rows per Second on a Laptop
Project Tungsten Phase II: Joining a Billion Rows per Second on a LaptopProject Tungsten Phase II: Joining a Billion Rows per Second on a Laptop
Project Tungsten Phase II: Joining a Billion Rows per Second on a Laptop
Databricks
 
Copper: A high performance workflow engine
Copper: A high performance workflow engineCopper: A high performance workflow engine
Copper: A high performance workflow engine
dmoebius
 
Getting started with Clojure
Getting started with ClojureGetting started with Clojure
Getting started with Clojure
John Stevenson
 
Java Memory Model
Java Memory ModelJava Memory Model
Java Memory Model
Łukasz Koniecki
 
Server side JavaScript: going all the way
Server side JavaScript: going all the wayServer side JavaScript: going all the way
Server side JavaScript: going all the way
Oleg Podsechin
 
NET Systems Programming Learned the Hard Way.pptx
NET Systems Programming Learned the Hard Way.pptxNET Systems Programming Learned the Hard Way.pptx
NET Systems Programming Learned the Hard Way.pptx
petabridge
 
ZFConf 2011: Что такое Sphinx, зачем он вообще нужен и как его использовать с...
ZFConf 2011: Что такое Sphinx, зачем он вообще нужен и как его использовать с...ZFConf 2011: Что такое Sphinx, зачем он вообще нужен и как его использовать с...
ZFConf 2011: Что такое Sphinx, зачем он вообще нужен и как его использовать с...
ZFConf Conference
 
Recipes for Running Spark Streaming Applications in Production-(Tathagata Das...
Recipes for Running Spark Streaming Applications in Production-(Tathagata Das...Recipes for Running Spark Streaming Applications in Production-(Tathagata Das...
Recipes for Running Spark Streaming Applications in Production-(Tathagata Das...
Spark Summit
 
Quantifying Container Runtime Performance: OSCON 2017 Open Container Day
Quantifying Container Runtime Performance: OSCON 2017 Open Container DayQuantifying Container Runtime Performance: OSCON 2017 Open Container Day
Quantifying Container Runtime Performance: OSCON 2017 Open Container Day
Phil Estes
 
Python twisted
Python twistedPython twisted
Python twisted
Mahendra M
 
FBTFTP: an opensource framework to build dynamic tftp servers
FBTFTP: an opensource framework to build dynamic tftp serversFBTFTP: an opensource framework to build dynamic tftp servers
FBTFTP: an opensource framework to build dynamic tftp servers
Angelo Failla
 
A Scalable I/O Manager for GHC
A Scalable I/O Manager for GHCA Scalable I/O Manager for GHC
A Scalable I/O Manager for GHC
Johan Tibell
 

Similar to Sedna XML Database: Executor Internals (20)

Leveraging Azure Databricks to minimize time to insight by combining Batch an...
Leveraging Azure Databricks to minimize time to insight by combining Batch an...Leveraging Azure Databricks to minimize time to insight by combining Batch an...
Leveraging Azure Databricks to minimize time to insight by combining Batch an...
 
Flink internals web
Flink internals web Flink internals web
Flink internals web
 
Data-and-Compute-Intensive processing Use Case: Lucene Domain Index
Data-and-Compute-Intensive processing Use Case: Lucene Domain IndexData-and-Compute-Intensive processing Use Case: Lucene Domain Index
Data-and-Compute-Intensive processing Use Case: Lucene Domain Index
 
Deep Learning and TensorFlow
Deep Learning and TensorFlowDeep Learning and TensorFlow
Deep Learning and TensorFlow
 
Kerberizing spark. Spark Summit east
Kerberizing spark. Spark Summit eastKerberizing spark. Spark Summit east
Kerberizing spark. Spark Summit east
 
Apache Spark Workshop, Apr. 2016, Euangelos Linardos
Apache Spark Workshop, Apr. 2016, Euangelos LinardosApache Spark Workshop, Apr. 2016, Euangelos Linardos
Apache Spark Workshop, Apr. 2016, Euangelos Linardos
 
Accelerated data access
Accelerated data accessAccelerated data access
Accelerated data access
 
The post release technologies of Crysis 3 (Slides Only) - Stewart Needham
The post release technologies of Crysis 3 (Slides Only) - Stewart NeedhamThe post release technologies of Crysis 3 (Slides Only) - Stewart Needham
The post release technologies of Crysis 3 (Slides Only) - Stewart Needham
 
Project Tungsten Phase II: Joining a Billion Rows per Second on a Laptop
Project Tungsten Phase II: Joining a Billion Rows per Second on a LaptopProject Tungsten Phase II: Joining a Billion Rows per Second on a Laptop
Project Tungsten Phase II: Joining a Billion Rows per Second on a Laptop
 
Copper: A high performance workflow engine
Copper: A high performance workflow engineCopper: A high performance workflow engine
Copper: A high performance workflow engine
 
Getting started with Clojure
Getting started with ClojureGetting started with Clojure
Getting started with Clojure
 
Java Memory Model
Java Memory ModelJava Memory Model
Java Memory Model
 
Server side JavaScript: going all the way
Server side JavaScript: going all the wayServer side JavaScript: going all the way
Server side JavaScript: going all the way
 
NET Systems Programming Learned the Hard Way.pptx
NET Systems Programming Learned the Hard Way.pptxNET Systems Programming Learned the Hard Way.pptx
NET Systems Programming Learned the Hard Way.pptx
 
ZFConf 2011: Что такое Sphinx, зачем он вообще нужен и как его использовать с...
ZFConf 2011: Что такое Sphinx, зачем он вообще нужен и как его использовать с...ZFConf 2011: Что такое Sphinx, зачем он вообще нужен и как его использовать с...
ZFConf 2011: Что такое Sphinx, зачем он вообще нужен и как его использовать с...
 
Recipes for Running Spark Streaming Applications in Production-(Tathagata Das...
Recipes for Running Spark Streaming Applications in Production-(Tathagata Das...Recipes for Running Spark Streaming Applications in Production-(Tathagata Das...
Recipes for Running Spark Streaming Applications in Production-(Tathagata Das...
 
Quantifying Container Runtime Performance: OSCON 2017 Open Container Day
Quantifying Container Runtime Performance: OSCON 2017 Open Container DayQuantifying Container Runtime Performance: OSCON 2017 Open Container Day
Quantifying Container Runtime Performance: OSCON 2017 Open Container Day
 
Python twisted
Python twistedPython twisted
Python twisted
 
FBTFTP: an opensource framework to build dynamic tftp servers
FBTFTP: an opensource framework to build dynamic tftp serversFBTFTP: an opensource framework to build dynamic tftp servers
FBTFTP: an opensource framework to build dynamic tftp servers
 
A Scalable I/O Manager for GHC
A Scalable I/O Manager for GHCA Scalable I/O Manager for GHC
A Scalable I/O Manager for GHC
 

Recently uploaded

HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
panagenda
 
Recommendation System using RAG Architecture
Recommendation System using RAG ArchitectureRecommendation System using RAG Architecture
Recommendation System using RAG Architecture
fredae14
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
innovationoecd
 
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxOcean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
SitimaJohn
 
Webinar: Designing a schema for a Data Warehouse
Webinar: Designing a schema for a Data WarehouseWebinar: Designing a schema for a Data Warehouse
Webinar: Designing a schema for a Data Warehouse
Federico Razzoli
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Alpen-Adria-Universität
 
Mariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceXMariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceX
Mariano Tinti
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
danishmna97
 
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Malak Abu Hammad
 
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfHow to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
Chart Kalyan
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
Wouter Lemaire
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
Pixlogix Infotech
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Tosin Akinosho
 
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success StoryDriving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Safe Software
 
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and MilvusBuilding Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
Zilliz
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Zilliz
 
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
Edge AI and Vision Alliance
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
Jakub Marek
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
akankshawande
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
Daiki Mogmet Ito
 

Recently uploaded (20)

HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
 
Recommendation System using RAG Architecture
Recommendation System using RAG ArchitectureRecommendation System using RAG Architecture
Recommendation System using RAG Architecture
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
 
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxOcean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
 
Webinar: Designing a schema for a Data Warehouse
Webinar: Designing a schema for a Data WarehouseWebinar: Designing a schema for a Data Warehouse
Webinar: Designing a schema for a Data Warehouse
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
 
Mariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceXMariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceX
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
 
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
 
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfHow to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
 
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success StoryDriving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
 
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and MilvusBuilding Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
 
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
 

Sedna XML Database: Executor Internals