Load and Transform Guide Version 2.2.0 Table of Contents

Total Page：16

File Type：pdf, Size：1020Kb

Load and Transform Guide Version 2.2.0 Table of Contents 1. About This Document . 5 1.1. Intended Audience . 5 1.2. New and Changed Information . 5 1.3. Notation Conventions . 6 1.4. Comments Encouraged . 8 2. Introduction . 9 2.1. Load Methods . 9 2.1.1. Insert Types . 11 2.2. Unload . 12 3. Tables and Indexes . 13 3.1. Choose Primary Key . 13 3.2. Salting . 13 3.3. Compression and Encoding . 14 3.4. Create Tables and Indexes . 14 3.5. Update Statistics . 15 3.5.1. Default Sampling . 15 3.6. Generate Single-Column and Multi-Column Histograms From One Statement . 16 3.6.1. Enable Update Statistics Automation . 16 3.6.2. Regenerate Histograms . 17 4. Bulk Load . 18 4.1. Load Data From Trafodion Tables . 18 4.1.1. Example . 18 4.2. Load Data From HDFS Files . 18 4.2.1. Example . 19 4.3. Load Data From Hive Tables . 20 4.3.1. Example . 21 4.4. Load Data From External Databases . 21 4.4.1. Install Required Software . 22 4.4.2. Sample Sqoop Commands . 22 4.4.3. Example . 23 5. Trickle Load . 24 5.1. Improving Throughput . 24 5.2. odb . 25 5.2.1. odb Throughput . 26 5.2.2. odb Load . 27 5.2.3. odb Copy . 29 5.2.4. odb Extract . 30 5.2.5. odb Transform . 32 6. Bulk Unload . 35 7. Monitor Progress . 36 7.1. INSERT and UPSERT . 36 7.2. UPSERT USING LOAD . 36 7.3. LOAD . 36 8. Troubleshoot . 38 8.1. Improving Throughput . 38 8.1.1. Tuplelists or Rowsets . 38 8.1.2. Native HBase Tables . 38 8.1.3. Hive Tables . ..

Copy Link

Recommended publications

Modern Technologies of Bigdata Analytics: Case Study on Hadoop Platform Dharminder Yadav1, Umesh Chandra2
International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) Web Site: www.ijettcs.org Email: [email protected] Volume 6, Issue 4, July- August 2017 ISSN 2278-6856 Modern Technologies of BigData Analytics: Case study on Hadoop Platform Dharminder Yadav1, Umesh Chandra2 1Research Scholar, Computer Science Department, Glocal University, Saharanpur, UP, India 2PhD, Assistant Professor, Computer Science Department, Glocal University, Saharanpur, UP, India Abstract exchange, banking, on-line and on-site procuring [2]. Data is growing in the worldwide by daily activities, by using the Enormous Information as an examination subject from a hand-held devices, the Internet, and social media sites.This few focuses course of events, paper main discusses about data processing by using various geographic yield, disciplinary output, types of distributed tool of Hadoop.This present study cover most of the tools used papers, topical and theoretical advancement. The Big Data in Hadoop that help in parallel processing and MapReduce. challenges define in 6V's that are variety, velocity, volume, The day since BigData term introduced to database world , Hadoop act like a savior for most of the large, small value, veracity, and volatility [23]. organization. Researchers will definitely found a way through Hadoop to work huge data concept and most of the researchers are being done in the field of BigData analytics and data mining with the help of Hadoop. Keywords— Big Data, Hadoop, HDFS (Hadoop Distributed File System), NOSQL 1.INTRODUCTION Big Data provide storage and data processing facilities to Cloud computing [26]. Big data comes around 2005 but now it is used everywhere in daily life, which alludes to an expansive scope of informational collections practically difficult to manage, handle and prepare utilizing accessible Volume: Data is growing exponentially by daily activities regular apparatuses and information administration which we handle.
[Show full text]
Provisioning Guide Version 2.3.0 Table of Contents
Provisioning Guide Version 2.3.0 Table of Contents 1. About This Document . 3 1.1. Intended Audience . 3 1.2. New and Changed Information . 3 1.3. Notation Conventions . 4 1.4. Comments Encouraged . 6 2. Quick Start . 8 2.1. Download Binaries . 8 2.2. Unpack Installer and Server package . 9 2.3. Collect Information . 10 2.3.1. Java Location . 10 2.3.2. Data Nodes . 11 2.3.3. Distribution Manager URL . 11 2.4. Run Installer . 12 3. Introduction . 13 3.1. Security Considerations . 13 3.2. Provisioning Options . 14 3.3. Provisioning Activities . 14 3.4. Provisioning Master Node . 15 3.5. Trafodion Installer . 15 3.5.1. Usage . 16 3.5.2. Install vs. Upgrade . 17 3.5.3. Guided Setup . 17 3.5.4. Automated Setup . 17 3.6. Trafodion Provisioning Directories . 20 4. Requirements . 22 4.1. General Cluster and OS Requirements and Recommendations . 22 4.1.1. Hardware Requirements and Recommendations . 22 4.1.2. OS Requirements and Recommendations . 23 4.1.3. IP Ports . 24 4.2. Prerequisite Software . 25 4.2.1. Hadoop Software . 25 4.2.2. Software Packages . 25 4.3. Trafodion User IDs and Their Privileges . 26 4.3.1. Trafodion Runtime User . 26 4.3.2. Trafodion Provisioning User . 26 4.4. Recommended Configuration Changes . 28 4.4.1. Recommended Security Changes . 29 4.4.2. Recommended HDFS Configuration Changes . 29 4.4.3. Recommended HBase Configuration Changes . 29 5. Prepare . 31 5.1. Install Optional Workstation Software . 31 5.2. Configure Installation User ID .
[Show full text]
IBM Big SQL (With Hbase), Splice Major Contributor to the Apache Be a Major Determinant“ Machine (Which Incorporates Hbase Madlib Project
MarketReport Market Report Paper by Bloor Author Philip Howard Publish date December 2017 SQL Engines on Hadoop It is clear that“ Impala, LLAP, Hive, Spark and so on, perform significantly worse than products from vendors with a history in database technology. Author Philip Howard” Executive summary adoop is used for a lot of these are discussed in detail in this different purposes and one paper it is worth briefly explaining H major subset of the overall that SQL support has two aspects: the Hadoop market is to run SQL against version supported (ANSI standard 1992, Hadoop. This might seem contrary 1999, 2003, 2011 and so on) plus the to Hadoop’s NoSQL roots, but the robustness of the engine at supporting truth is that there are lots of existing SQL queries running with multiple investments in SQL applications that concurrent thread and at scale. companies want to preserve; all the Figure 1 illustrates an abbreviated leading business intelligence and version of the results of our research. analytics platforms run using SQL; and This shows various leading vendors, SQL skills, capabilities and developers and our estimates of their product’s are readily available, which is often not positioning relative to performance and The key the case for other languages. SQL support. Use cases are shown by the differentiators“ However, the market for SQL engines on colour of each bubble but for practical between products Hadoop is not mono-cultural. There are reasons this means that no vendor/ multiple use cases for deploying SQL on product is shown for more than two use are the use cases Hadoop and there are more than twenty cases, which is why we describe Figure they support, their different SQL on Hadoop platforms.
[Show full text]
Esgyndb 版本说明2.4.2
EsgynDB 版本说明 2.4.2 2018 年 7 月版权 © Copyright 2018 Esgyn 公告本文档包含的信息如有更改，恕不另行通知。保留所有权利。除非版权法允许，否则在未经 Esgyn 预先书面许可的情况下，严禁改编或翻译本手册的内容。Esgyn 对于本文中所包含的技术或编辑错误、遗漏概不负责。 Esgyn 产品和服务附带的正式担保声明中规定的担保是该产品和服务享有的唯一担保。本文中的任何信息均不构成额外的保修条款。声明 Microsoft® 和 Windows® 是美国微软公司的注册商标。Java® 和 MySQL® 是 Oracle 及其子公司的注册商标。Bosun 是 Stack Exchange 的商标。Apache®、 Hadoop®、HBase®、Hive®、openTSDB®、Sqoop® 和 Trafodion® 是 Apache 软件基金会的商标。Esgyn 和 EsgynDB 是 Esgyn 的商标。目录 1. 功能 ........................................................................................................ 2 EsgynDB 2.4.2 ................................................................................................... 2 EsgynDB 2.4.1 ................................................................................................... 2 EsgynDB 2.4.0 ................................................................................................... 2 2. 迁移要点................................................................................................ 3 2.1 在 EsgynDB 2.3.0 的基础上升级 ..................................................................... 3 2.1.1 系统 .......................................................................................................... 3 2.1.2 应用程序 .................................................................................................. 4 2.2 在 EsgynDB 2.2.0 或更早版本的基础上升级 ................................................. 5 2.2.1 系统 .......................................................................................................... 5 2.2.2 TRAF_HOME ..........................................................................................
[Show full text]
Diplomová Práce
Vysoká škola ekonomická v Praze Fakulta informatiky a statistiky Komparace distribucí frameworku Apache Hadoop DIPLOMOVÁ PRÁCE Studijní program: Aplikovaná informatika Studijní obor: Podniková informatika Autor: Mgr. Petr Todorov Vedoucí diplomové práce: doc. Ing. Ota Novotný, Ph.D. Praha, duben 2020 Prohlášení Prohlašuji, že jsem diplomovou práci Komparace distribucí frameworku Apache Hadoop vypracoval samostatně za použití v práci uvedených pramenů a literatury. V Praze dne 27. dubna 2020 ........................................................ Petr Todorov Poděkování Na tomto místě bych rád poděkoval především doc. Ing. Otovi Novotnému, Ph.D., za cenné rady, konzultace a metodické vedení při tvorbě této diplomové práce. Současně bych chtěl poděkovat své rodině za podporu nejen při tvorbě této práce, ale po celou dobu studia na Vysoké škole ekonomické. Abstrakt Práce se zaměřuje na komparaci distribucí frameworku pro zpracování big data Apache Hadoop. Teoretická část přináší stručný vhled do oblasti big data, detailní popis frameworku a ekosystému Apache Hadoop. Práce rovněž poskytuje přehled o situaci na trhu distribucí frameworku pro zpracování big data Apache Hadoop. Praktická část práce představuje možnosti zpracování big data v reálném čase v rámci vybraných distribucí frameworku Apache Hadoop formou realizace typové úlohy příjmu a zpracování příspěvků ze sociální sítě Twitter. Na základě zjištěných informací a výsledků provedení příjmu a zpracování big data je následně provedena komparace vybraných distribucí frameworku Apache Hadoop. Informace, které práce přináší, lze využít pro rychlou orientaci na trhu distribucí frameworku Apache Hadoop a výběr distribuce frameworku Apache Hadoop vhodné pro zpracování big data v reálném čase. Klíčová slova Big data, Apache Hadoop, Cloudera, Hortonworks, MapR, zpracování big data v reálném čase. JEL klasifikace C88 Other Computer Software, L86 Information and Internet Services • Computer Software, M15 IT Management.
[Show full text]
Stored Procedures in Java (Spjs) Guide Version 2.1.0 Table of Contents
Stored Procedures in Java (SPJs) Guide Version 2.1.0 Table of Contents 1. About This Document . 4 1.1. Intended Audience . 4 1.2. Document Organization . 4 1.3. New and Changed Information . 5 1.4. Notation Conventions . 5 1.5. Comments Encouraged . 8 2. Introduction . 9 2.1. What Is an SPJ? . 9 2.2. Benefits of SPJs . 9 2.2.1. Java Methods Callable From SQL . 10 2.2.2. Common Packaging Technique . 10 2.2.3. Security . 10 2.2.4. Increased Productivity . 10 2.2.5. Portability . 11 2.3. Use SPJs . 12 3. Get Started . 15 3.1. Required Client Software . 15 3.1.1. Java Development Kit . 15 3.2. Recommended Client Software . 16 3.2.1. Trafodion Command Interface (trafci) . 16 3.2.2. HP JDBC Type 4 Driver . 16 4. Develop SPJ Methods . 17 4.1. Guidelines for Writing SPJ Methods . 17 4.1.1. Signature of the Java Method . 17 4.1.2. Returning Output Values From the Java Method . 19 4.1.3. Returning Stored Procedure Result Sets . 20 4.1.4. Using the main() Method . 22 4.1.5. Null Input and Output . 23 4.1.6. Static Java Variables . 23 4.1.7. Nested Java Method Invocations . 23 4.2. Accessing Trafodion . 24 4.2.1. Use of java.sql.Connection Objects . 24 4.2.2. Using JDBC Method Calls . 26 4.2.3. Referring to Database Objects in an SPJ Method . 27 4.2.4. Using the SESSION_USER or CURRENT_USER Function in an SPJ Method . 29 4.2.5.
[Show full text]
Provisioning Guide Version 2.0.0 Table of Contents
Provisioning Guide Version 2.0.0 Table of Contents 1. About This Document . 3 1.1. Intended Audience . 3 1.2. New and Changed Information . 3 1.3. Notation Conventions . 4 1.4. Comments Encouraged . 6 2. Introduction . 8 2.1. Security Considerations . 8 2.2. Provisioning Options . 9 2.3. Provisioning Activities . 9 2.4. Provisioning Master Node . 10 2.5. Trafodion Installer . 10 2.5.1. Usage . 11 2.5.2. Install vs. Upgrade . 12 2.5.3. Guided Setup . 12 2.5.4. Automated Setup . 12 2.6. Trafodion Provisioning Directories . 17 3. Requirements . 18 3.1. General Cluster and OS Requirements and Recommendations . 18 3.1.1. Hardware Requirements and Recommendations . 18 3.1.2. OS Requirements and Recommendations . 19 3.1.3. IP Ports . 20 3.2. Prerequisite Software . 21 3.2.1. Hadoop Software . 21 3.2.2. Software Packages . 22 3.3. Trafodion User IDs and Their Privileges . 23 3.3.1. Trafodion Runtime User . 23 3.3.2. Trafodion Provisioning User . 23 3.4. Required Configuration Changes . 25 3.4.1. Operating System Changes . 25 3.4.2. ZooKeeper Changes . 26 3.4.3. HDFS Changes . 26 3.4.4. HBase Changes . 27 3.5. Recommended Configuration Changes . 28 3.5.1. Recommended Security Changes . 28 3.5.2. Recommended HDFS Configuration Changes . 28 3.5.3. Recommended HBase Configuration Changes . 29 4. Prepare . 30 4.1. Install Optional Workstation Software . 30 4.2. Configure Installation User ID . 30 4.3. Disable requiretty . 31 4.4. Verify OS Requirements and Recommendations . 31 4.5.
[Show full text]
Client Installation Guide Version 1.3.0 Table of Contents
Client Installation Guide Version 1.3.0 Table of Contents 1. About This Document . 2 1.1. Intended Audience . 2 1.2. New and Changed Information . 2 1.3. Notation Conventions . 2 1.4. Comments Encouraged . 5 2. Introduction . 6 2.1. Client Summary . 6 2.1.1. JDBC-Based Clients . 6 2.1.2. ODBC-Based Clients . 6 2.2. Download Installation Package . 7 2.2.1. Windows Download . 7 2.2.2. Linux Download . 8 3. Install JDBC Type-4 Driver . 9 3.1. Installation Requirements . 9 3.1.1. Java Environment . 9 3.2. Installation Instructions . 14 3.2.1. Install JDBC Type-4 Driver . 14 3.3. Set Up Client Environment . 15 3.3.1. Java Development . 15 3.3.2. Configure Applications . 16 3.4. Test Programs . 17 3.5. Uninstall JDBC Type-4 Driver . 19 3.6. Reinstall JDBC Type-4 Driver . 21 4. Install trafci . 22 4.1. Installation Requirements . 22 4.1.1. Install Perl or Python . 22 4.2. Installation Instructions . 23 4.2.1. Run Executable JAR Installer . 23 4.3. Post-Installation Instructions . 35 4.3.1. Verify Installed Software Files . 35 4.4. Test Launching trafci . 36 4.4.1. Windows Example . 37 4.4.2. Linux Example . 38 4.5. Uninstall trafci . 39 5. Configure DbVisualizer . 40 5.1. Prerequisite Software . 40 5.2. Configuration Instructions . 40 5.2.1. Disable Connection Validation Select Option . 40 5.2.2. Register JDBC Type-4 Driver . 42 5.2.3. Connect to Trafodion . 43 6. Configure SQuirreL Client . 44 6.1.
[Show full text]
ASF FY2021 Annual Report
0 Contents The ASF at-a-Glance 4 President’s Report 6 Treasurer’s Report 8 FY2021 Financial Statement 12 Fundraising 14 Legal Affairs 19 Infrastructure 21 Security 22 Data Privacy 25 Marketing & Publicity 26 Brand Management 40 Conferences 43 Community Development 44 Diversity & Inclusion 46 Projects and Code 48 Contributions 65 ASF Members 72 Emeritus Members 77 Memorial 78 Contact 79 FY2021 Annual Report Page 1 The ASF at-a-Glance "The Switzerland of Open Source..." — Matt Asay, InfoWorld The World’s Largest Open Source Foundation The Apache Software Foundation (ASF) incorporated in 1999 with the mission of providing software for the common good. Today the ASF is the world’s largest Open Source foundation, stewarding 227M+ lines of code and providing $22B+ worth of software to the public at 100% no cost. ASF projects are integral to nearly every aspect of modern computing, beneﬁtting billions worldwide. Change Agents The ASF was founded by developers of the Apache HTTP Server to protect the core interests of those contributing to and using our open source projects. The ASF’s all-volunteer community now includes over 8,200 committers, involved in over 350 projects that have been organized by about 200 independent project management committees, and is overseen by 850+ ASF members. The Foundation is a globally-distributed, virtual organization with contributors on every continent. Apache projects power countless mission-critical solutions worldwide, and have spearheaded industry breakthroughs in dozens of categories, from Big Data to Web Frameworks. More than three dozen future projects and their communities are currently being mentored in the Apache Incubator.
[Show full text]
Provisioning Guide Version 2.1.0 Table of Contents
Provisioning Guide Version 2.1.0 Table of Contents 1. About This Document . 2 1.1. Intended Audience . 2 1.2. New and Changed Information . 2 1.3. Notation Conventions . 3 1.4. Comments Encouraged . 5 2. Quick Start . 7 2.1. Download Binaries . 7 2.2. Unpack Installer . 8 2.3. Collect Information . 9 2.3.1. Location of Trafodion Server-Side Binary . 9 2.3.2. Java Location . 9 2.3.3. Data Nodes . 10 2.3.4. Trafodion Runtime User Home Directory . 10 2.3.5. Distribution Manager URL . 10 2.4. Run Installer . 11 3. Introduction . 20 3.1. Security Considerations . 20 3.2. Provisioning Options . 21 3.3. Provisioning Activities . 22 3.4. Provisioning Master Node . 22 3.5. Trafodion Installer . 23 3.5.1. Usage . 24 3.5.2. Install vs. Upgrade . 25 3.5.3. Guided Setup . 25 3.5.4. Automated Setup . 25 3.6. Trafodion Provisioning Directories . 31 4. Requirements . 32 4.1. General Cluster and OS Requirements and Recommendations . 32 4.1.1. Hardware Requirements and Recommendations . 32 4.1.2. OS Requirements and Recommendations . 33 4.1.3. IP Ports . 34 4.2. Prerequisite Software . 35 4.2.1. Hadoop Software . 35 4.2.2. Software Packages . 36 4.3. Trafodion User IDs and Their Privileges . 37 4.3.1. Trafodion Runtime User . 37 4.3.2. Trafodion Provisioning User . 37 4.4. Required Configuration Changes . 39 4.4.1. Operating System Changes . 40 4.4.2. ZooKeeper Changes . 41 4.4.3. HDFS Changes . 41 4.4.4.
[Show full text]
Esgyndb版本说明2.4.1 (中文版)
EsgynDB 版本说明 2.4.1 2018 年 5 月版权 © Copyright 2018 Esgyn 公告本文档包含的信息如有更改，恕不另行通知。保留所有权利。除非版权法允许，否则在未经 Esgyn 预先书面许可的情况下，严禁改编或翻译本手册的内容。Esgyn 对于本文中所包含的技术或编辑错误、遗漏概不负责。 Esgyn 产品和服务附带的正式担保声明中规定的担保是该产品和服务享有的唯一担保。本文中的任何信息均不构成额外的保修条款。声明 Microsoft® 和 Windows® 是美国微软公司的注册商标。Java® 和 MySQL® 是 Oracle 及其子公司的注册商标。Bosun 是 Stack Exchange 的商标。Apache®、 Hadoop®、HBase®、Hive®、openTSDB®、Sqoop® 和 Trafodion® 是 Apache 软件基金会的商标。Esgyn 和 EsgynDB 是 Esgyn 的商标。目录 1. 功能 ............................................................................................................... 2 EsgynDB 2.4.1 ................................................................................................... 2 EsgynDB 2.4.0 ................................................................................................... 2 2. 迁移要点 ...................................................................................................... 3 2.1 在 EsgynDB 2.3.0 的基础上升级 ..................................................................... 3 2.1.1 系统 .......................................................................................................... 3 2.1.2 应用程序 .................................................................................................. 4 2.2 在 EsgynDB 2.2.0 或更早版本的基础上升级 ................................................. 5 2.2.1 系统 .......................................................................................................... 5 2.2.2 TRAF_HOME ........................................................................................... 5 2.2.3 日志文件 .................................................................................................
[Show full text]
Client Installation Guide Version 2.2.0 Table of Contents
Client Installation Guide Version 2.2.0 Table of Contents 1. About This Document . 5 1.1. Intended Audience . 5 1.2. New and Changed Information . 5 1.3. Notation Conventions . 5 1.4. Comments Encouraged . 8 2. Introduction . 9 2.1. Client Summary . 9 2.1.1. JDBC-Based Clients . 9 2.1.2. ODBC-Based Clients . 9 3. Preparation . 10 3.1. Java Setup . 10 3.1.1. Verify Java Version . 10 3.1.2. Install Java . 11 3.2. Download Client Software . 11 3.2.1. Windows Download . 12 3.2.2. Linux Download . 13 3.3. Unpack Client Software . 14 3.3.1. Unpack JDBC-Based Client Software . 14 3.3.2. Unpack ODBC-Based Client Software . 15 4. Install JDBC Type-4 Driver . 16 4.1. Prerequisites . 16 4.2. Validate Install Directory . 16 4.3. Set Up Client Environment . 17 4.3.1. Java Development . 17 4.3.2. Configure Applications . 18 4.4. Test Programs . 19 4.5. Uninstall JDBC Type-4 Driver . 23 5. Install trafci . 24 5.1. Prerequisites . 24 5.2. Install Perl or Python . 24 5.3. Verify Installation . 25 5.4. Run trafci Installer . 25 5.4.1. GUI Wizard Install . 25 5.4.2. Command-Line Installation Steps . 32 5.5. Verify Installed Software Files . 37 5.6. Modify PATH variable . 37 5.7. Test Launching trafci . 38 5.7.1. Windows Example . 38 5.7.2. Linux Example . 39 5.8. Uninstall trafci . 40 6. Configure DBVisualizer . 41 6.1. Prerequisites . 41 6.2. Configuration Instructions .
[Show full text]