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Apache Sqoop Cookbook : Unlocking Hadoop for Your Relational Database by Jarek Jarcec Cecho and Kathleen Ting (2013, Trade Paperback)
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About this product
Product Identifiers
PublisherO'reilly Media, Incorporated
ISBN-101449364624
ISBN-139781449364625
eBay Product ID (ePID)166235055
Product Key Features
Number of Pages91 Pages
Publication NameApache Sqoop Cookbook : Unlocking Hadoop for Your Relational Database
LanguageEnglish
SubjectProgramming Languages / General, Databases / Data Warehousing, Data Processing, Databases / Data Mining
Publication Year2013
TypeTextbook
AuthorJarek Jarcec Cecho, Kathleen Ting
Subject AreaComputers
FormatTrade Paperback
Dimensions
Item Height0.2 in
Item Weight6.3 Oz
Item Length9.2 in
Item Width7 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN2016-498284
Table Of ContentForeword;Preface; Sqoop 2; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Acknowledgments;Chapter 1: Getting Started; 1.1 Downloading and Installing Sqoop; 1.2 Installing JDBC Drivers; 1.3 Installing Specialized Connectors; 1.4 Starting Sqoop; 1.5 Getting Help with Sqoop;Chapter 2: Importing Data; 2.1 Transferring an Entire Table; 2.2 Specifying a Target Directory; 2.3 Importing Only a Subset of Data; 2.4 Protecting Your Password; 2.5 Using a File Format Other Than CSV; 2.6 Compressing Imported Data; 2.7 Speeding Up Transfers; 2.8 Overriding Type Mapping; 2.9 Controlling Parallelism; 2.10 Encoding NULL Values; 2.11 Importing All Your Tables;Chapter 3: Incremental Import; 3.1 Importing Only New Data; 3.2 Incrementally Importing Mutable Data; 3.3 Preserving the Last Imported Value; 3.4 Storing Passwords in the Metastore; 3.5 Overriding the Arguments to a Saved Job; 3.6 Sharing the Metastore Between Sqoop Clients;Chapter 4: Free-Form Query Import; 4.1 Importing Data from Two Tables; 4.2 Using Custom Boundary Queries; 4.3 Renaming Sqoop Job Instances; 4.4 Importing Queries with Duplicated Columns;Chapter 5: Export; 5.1 Transferring Data from Hadoop; 5.2 Inserting Data in Batches; 5.3 Exporting with All-or-Nothing Semantics; 5.4 Updating an Existing Data Set; 5.5 Updating or Inserting at the Same Time; 5.6 Using Stored Procedures; 5.7 Exporting into a Subset of Columns; 5.8 Encoding the NULL Value Differently; 5.9 Exporting Corrupted Data;Chapter 6: Hadoop Ecosystem Integration; 6.1 Scheduling Sqoop Jobs with Oozie; 6.2 Specifying Commands in Oozie; 6.3 Using Property Parameters in Oozie; 6.4 Installing JDBC Drivers in Oozie; 6.5 Importing Data Directly into Hive; 6.6 Using Partitioned Hive Tables; 6.7 Replacing Special Delimiters During Hive Import; 6.8 Using the Correct NULL String in Hive; 6.9 Importing Data into HBase; 6.10 Importing All Rows into HBase; 6.11 Improving Performance When Importing into HBase;Chapter 7: Specialized Connectors; 7.1 Overriding Imported boolean Values in PostgreSQL Direct Import; 7.2 Importing a Table Stored in Custom Schema in PostgreSQL; 7.3 Exporting into PostgreSQL Using pg_bulkload; 7.4 Connecting to MySQL; 7.5 Using Direct MySQL Import into Hive; 7.6 Using the upsert Feature When Exporting into MySQL; 7.7 Importing from Oracle; 7.8 Using Synonyms in Oracle; 7.9 Faster Transfers with Oracle; 7.10 Importing into Avro with OraOop; 7.11 Choosing the Proper Connector for Oracle; 7.12 Exporting into Teradata; 7.13 Using the Cloudera Teradata Connector; 7.14 Using Long Column Names in Teradata;Colophon;
SynopsisGiven that Sqoop was designed for power users, there is a need for a standalone recipe-based book on Sqoop that will cover common usage and use cases. the various options of the Sqoop Import and Export commands, Sqoop's integration with Oozie, Hive, HBase, special connectors, and common issues., Given that Sqoop was designed for power users, there is a need for a standalone recipe-based book on Sqoop that will cover common usage and use cases. the various options of the Sqoop Import and Export commands, Sqoop's integration with Oozie, Hive, HBase, special connectors, and common issues, Integrating data from multiple sources is essential in the age of big data, but it can be a challenging and time-consuming task. This handy cookbook provides dozens of ready-to-use recipes for using Apache Sqoop, the command-line interface application that optimizes data transfers between relational databases and Hadoop. Sqoop is both powerful and bewildering, but with this cookbook's problem-solution-discussion format, you'll quickly learn how to deploy and then apply Sqoop in your environment. The authors provide MySQL, Oracle, and PostgreSQL database examples on GitHub that you can easily adapt for SQL Server, Netezza, Teradata, or other relational systems. Transfer data from a single database table into your Hadoop ecosystem Keep table data and Hadoop in sync by importing data incrementally Import data from more than one database table Customize transferred data by calling various database functions Export generated, processed, or backed-up data from Hadoop to your database Run Sqoop within Oozie, Hadoop's specialized workflow scheduler Load data into Hadoop's data warehouse (Hive) or database (HBase) Handle installation, connection, and syntax issues common to specific database vendors
LC Classification NumberQA76.9
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