Advantages of Schema Less Database
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An Evaluation of Compilation-Based PL/PGSQL Execution Tanuj Nayak CMU-CS-21-101 February 2021
An Evaluation of Compilation-Based PL/PGSQL Execution Tanuj Nayak CMU-CS-21-101 February 2021 Computer Science Department School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Thesis Committee: Andy Pavlo (Chair) Todd C. Mowry Submitted in partial fulfillment of the requirements for the Fifth Year Master’s Program. Copyright © 2021 Tanuj Nayak Keywords: User Defined Functions, Compilation, Inlining Abstract User Defined Functions (UDFs) are an important analytical feature in modern Database Management Systems (DBMSs) due to their server-side execution proper- ties. These properties allow complex analytical queries to execute without serializing intermediate data over a network. However, query engines often incur significant overheads when executing UDFs due to them being non-declarative in contrast to SQL queries. This contrast causes a lot of context switching between UDF and SQL execution. As a given UDF invokes more SQL queries, these overheads become more noticeable. In this thesis, we investigate the extent to which compilation allow us to overcome such overheads. Compilation for executing SQL queries has become popu- lar in database research in the past decade, especially in the context of main memory DBMSs. It has been shown to deliver significant improvements to query execution performance. We compare the technique of compiling UDFs with query inlining, another recent UDF execution technique. To make this comparison, we implemented a UDF compilation framework in NoisePage, a main-memory compilation-based DBMS. In this framework we compile UDFs into a domain-specific language (DSL) function and evaluated it against query inlining. We find that this framework has greater support across UDF language features than inlining frameworks and allows for more efficient functions. -
CMU-CS-21-106 May 2021
On Building Robustness into Compilation-Based Main-Memory Database Query Engines Prashanth Menon CMU-CS-21-106 May 2021 School of Computer Science Computer Science Department Carnegie Mellon University Pittsburgh, PA 15213 Thesis Committee Andrew Pavlo (Co-Chair) Todd C. Mowry (Co-Chair) Jonathan Aldrich Thomas Neumann, Technische Universität München (TUM) Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Copyright © 2021 Prashanth Menon This research was sponsored by Google, Intel ISTC-CC, and the National Science Foundation under grant numbers CNS-1065112, IIS-1423210, CNS-1423172, IIS-1718582, and CCF-1822933. The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies, either expressed or implied, of any sponsoring institution, the U.S. government or any other entity. Keywords: Code Generation, Query Compilation, Adaptive Query Processing, Vectorized Pro- cessing To my family, here and yet to arrive. Abstract Relational database management systems (DBMS) are the bedrock upon which modern data pro- cessing intensive applications are assembled. Critical to ensuring low-latency queries is the effi- ciency of the DBMSs query processor. Just-in-time (JIT) query compilation is a popular technique to improve analytical query processing performance. However, a compiled query cannot overcome poor choices made by the DBMSs optimizer. A lousy query plan results in lousy query code. Poor query plans often arise and for many reasons. Although there is a large body of work exploring how a query processor can adapt itself at runtime to compensate for inadequate plans, these techniques do not work in DBMSs that rely on compiling queries. -
Scalable and Reactive Data Management for Mobile Internet-Of-Things Applications with Actor-Oriented Databases
UNIVERSITY OF COPENHAGEN PhD in Computer Science Scalable and Reactive Data Management for Mobile Internet-of-Things Applications with Actor-Oriented Databases Yiwen Wang Supervised by Marcos Antonio Vaz Salles April 2021 Yiwen Wang Scalable and Reactive Data Management for Mobile Internet-of-Things Applications with Actor-Oriented Databases PhD in Computer Science, April 2021 Supervisors: Marcos Antonio Vaz Salles University of Copenhagen Faculty of Science PhD Degree in Computer Science Sigurdsgade 41 2200 Copenhagen 四载春秋,畏作黄粱,虽非寒窗,亦是苦读。知己无柳絮高才,幸有大贤焉 而为其徒,博学慎思,人十能之而己百之,笃行亦则足恃矣。今停笔止言之 际,回首旦暮,赠以诗酒共年华,赚得知交满天下。愿今后去往之地,皆为 热土,期明朝漫漫修远之路,皆伴长风济沧海。 iii Acknowledgements My PhD work conducted in the context of the Future Cropping partnership (Fu- ture Cropping partnership website 2018), supported by Innovation Fund Den- mark. Experimental evaluation partially supported by the AWS Cloud Credits for Research program. In addition, this work was partly supported by the International Network Programme project "Modeling and Developing Actor Database Applications", funded by the Danish Agency for Science and Higher Education (number 7059-000528) and by FAPESP CEPID CCES 13/08293-7. Additional funding provided by FAPESP project 17/02325-5 and by CNPq- Brazil, Department of Computer Science, University of Copenhagen and Pro- gramming technology foundations for Accountability, Privacy-by-design & Robustness in Context-aware Systems (case number: 9131-00077B). Throughout the working of this nearly four years PhD pursuing adventure, I have received a great deal of support and assistance from many aspects. First and foremost, I would like to express my special appreciation to my supervisor, Professor Marcos Antonio Vaz Salles, whose expertise was invaluable in guiding me in the research. -
AWS Glue Studio User Guide AWS Glue Studio User Guide
AWS Glue Studio User Guide AWS Glue Studio User Guide AWS Glue Studio: User Guide Copyright © Amazon Web Services, Inc. and/or its affiliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. AWS Glue Studio User Guide Table of Contents What is AWS Glue Studio? ................................................................................................................... 1 Features of AWS Glue Studio ....................................................................................................... 2 Visual job editor ................................................................................................................ 2 Job script code editor ......................................................................................................... 2 Job performance dashboard ................................................................................................ 3 Support for dataset partitioning .......................................................................................... 3 When should I use AWS Glue Studio? ........................................................................................... 3 Accessing AWS Glue Studio ........................................................................................................ -
732A54 / TDDE31 Big Data Analytics Topic: Dbmss for Big
732A54 / TDDE31 Big Data Analytics Topic: DBMSs for Big Data Olaf Hartig [email protected] Relational Database Management Systems ● Well-defined formal foundations (relational data model) schema instance/ state Figure from “Fundamentals of Database Systems” by Elmasri and Navathe, Addison Wesley. 732A54 / TDDE31 Big Data Analytics Topic: Database Management Systems for Big Data Olaf Hartig 2 Relational Database Management Systems ● Well-defined formal foundations (relational data model) ● SQL – powerful declarative language – querying – data manipulation – database definition ● Support of transactions with ACID properties (Atomicity, Consistency preservation, Isolation, Durability) ● Established technology (developed since the 1970s) – many vendors – highly mature systems – experienced users and administrators 732A54 / TDDE31 Big Data Analytics Topic: Database Management Systems for Big Data Olaf Hartig 3 Business world has evolved ● Organizations and companies (whole industries) shift to the digital economy powered by the Internet ● Central aspect: new IT applications that allow companies to run their business and to interact with costumers – Web applications – Mobile applications – Connected devices (“Internet of Things”) Image source: https://pixabay.com/en/technology-information-digital-2082642/ 732A54 / TDDE31 Big Data Analytics Topic: Database Management Systems for Big Data Olaf Hartig 4 New Challenges for Database Systems ● Increasing numbers of concurrent users/clients – tens of thousands, perhaps millions – globally distributed