Hadoop Real World Solutions Cookbook
Jonathan. Owens
Bok Engelsk 2013 · Electronic books.
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| Utgitt | Birmingham : : Packt Publishing, , 2013.
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| Omfang | 1 online resource (316 p.)
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| Opplysninger | Description based upon print version of record.. - Cover; Copyright; Credits; About the Authors; About the Reviewers; www.packtpub.com; Table of Contents; Preface; Chapter 1: Hadoop Distributed File System - Importing and Exporting Data; Introduction; Importing and exporting data into HDFS using Hadoop shell commands; Moving data efficiently between clusters using Distributed Copy; Importing data from MySQL into HDFS using Sqoop; Exporting data from HDFS into MySQL using Sqoop; Configuring Sqoop for Microsoft SQL Server; Exporting data from HDFS into MongoDB; Importing data from MongoDB into HDFS. - Chapter 4: Performing Common Tasks Using Hive, Pig, and MapReduceIntroduction; Using Hive to map an external table over weblog data in HDFS; Using Hive to dynamically create tables from the results of a weblog query; Using the Hive string UDFs to concatenate fields in weblog data; Using Hive to intersect weblog IPs and determine the country; Generating n-grams over news archives using MapReduce; Using the distributed cache in MapReduce; to find lines that contain matching keywords over news archives; Using Pig to load a table and perform a SELECT operation with GROUP BY. - Chapter 5: Advanced JoinsIntroduction; Joining data in the Mapper using MapReduce; Joining data using Apache Pig replicated join; Joining sorted data using Apache Pig merge join; Joining skewed data using Apache Pig skewed join; Using a map-side join in Apache Hive to analyze geographical events; Using optimized full outer joins in Apache Hive to analyze geographical events; Joining data using an external key-value store (Redis); Chapter 6: Big Data Analysis; Introduction; Counting distinct IPs in web log data using MapReduce and Combiners. - Exporting data from HDFS into MongoDB using PigUsing HDFS in a Greenplum external table; Using Flume to load data into HDFS; Chapter 2: HDFS; Introduction; Reading and writing data to HDFS; Compressing data using LZO; Reading and writing data to SequenceFiles; Using Apache Avro to serialize data; Using Apache Thrift to serialize data; Using Protocol Buffers to serialize data; Setting the replication factor for HDFS; Setting the block size for HDFS; Chapter 3: Extracting and Transforming Data; Introduction; Transforming Apache logs into TSV format using MapReduce. - Using Apache Pig to filter bot traffic from web server logsUsing Apache Pig to sort web server log data by timestamp; Using Apache Pig to sessionize web server log data; Using Python to extend Apache Pig functionality; Using MapReduce and secondary sort to calculate page views; Using Hive and Python to clean and transform geographical event data; Using Python and Hadoop Streaming to perform a time series analytic; Using MultipleOutputs in MapReduce to name output files; Creating custom Hadoop Writable and InputFormat to read geographical event data. - Using Hive date UDFs to transform and sort event dates from geographic event data. - Realistic, simple code examples to solve problems at scale with Hadoop and related technologies.
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| Dewey | |
| ISBN | 9781849519120
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