000			03739cam a2200397Ka 4500
020			_a9781119254805 _q(electronic bk.)
020			_a1119254809 _q(electronic bk.)
020			_a9781119254041 _q(electronic bk.)
020			_a1119254043 _q(electronic bk.)
020			_a9781119254058 _q(electronic bk.)
020			_a1119254051 _q(electronic bk.)
020			_z9781119254010
020			_z1119254019
037			_a981A916F-B662-49E4-841E-31BB904FAAC4 _bOverDrive, Inc. _nhttp://www.overdrive.com
040			_cCUS
072		7	_aCOM _x000000 _2bisacsh
100	1		_aGanelin, Ilya.
245	1	0	_aSpark : _bbig data cluster computing in production / _cIlya Ganelin [and others].
260		1	_aIndianapolis, IN : _bWiley, _c[2016]
260		4	_c©2016
300			_a1 online resource (219 pages)
505	0		_aSpark"!Big Data Cluster Computing in Production; About the Authors; About the Technical Editors; Credits; Acknowledgments; Contents at a glance; Contents; Introduction; Chapter 1 Finishing Your Spark Job; Installation of the Necessary Components; Native Installation Using a Spark Standalone Cluster; The History of Distributed Computing That Led to Spark; Enter the Cloud; Understanding Resource Management; Using Various Formats for Storage; Text Files; Sequence Files; Avro Files; Parquet Files; Making Sense of Monitoring and Instrumentation; Spark UI; Spark Standalone UI; Metrics REST API.
505	8		_aMetrics SystemExternal Monitoring Tools; Summary; Chapter 2 Cluster Management; Background; Spark Components; Driver; Workers and Executors; Configuration; Spark Standalone; Architecture; Single-Node Setup Scenario; Multi-Node Setup; YARN; Architecture; Dynamic Resource Allocation; Scenario; Mesos; Setup; Architecture; Dynamic Resource Allocation; Basic Setup Scenario; Comparison; Summary; Chapter 3 Performance Tuning; Spark Execution Model; Partitioning; Controlling Parallelism; Partitioners; Shuffling Data; Shuffling and Data Partitioning; Operators and Shuffling.
505	8		_aShuffling Is Not That Bad After AllSerialization; Kryo Registrators; Spark Cache; Spark SQL Cache; Memory Management; Garbage Collection; Shared Variables; Broadcast Variables; Accumulators; Data Locality; Summary; Chapter 4 Security; Architecture; Security Manager; Setup Configurations; ACL; Configuration; Job Submission; Web UI; Network Security; Encryption; Event logging; Kerberos; Apache Sentry; Summary; Chapter 5 Fault Tolerance or Job Execution; Lifecycle of a Spark Job; Spark Master; Spark Driver; Spark Worker; Job Lifecycle; Job Scheduling; Scheduling within an Application.
505	8		_aScheduling with External UtilitiesFault Tolerance; Internal and External Fault Tolerance; Service Level Agreements (SLAs); Resilient Distributed Datasets (RDDs); Batch versus Streaming; Testing Strategies; Recommended Configurations; Summary; Chapter 6 Beyond Spark; Data Warehousing; Spark SQL CLI; Thrift JDBC/ODBC Server; Hive on Spark; Machine Learning; DataFrame; MLlib and ML; Mahout on Spark; Hivemall on Spark; External Frameworks; Spark Package; XGBoost; spark-jobserver; Future Works; Integration with the Parameter Server; Deep Learning; Enterprise Usage.
505	8		_aCollecting User Activity Log with Spark and KafkaReal-Time Recommendation with Spark; Real-Time Categorization of Twitter Bots; Summary; Index; EULA.
630	0	0	_aSPARK (Electronic resource)
630	0	7	_aSPARK (Electronic resource) _2fast _0(OCoLC)fst01400497
650		0	_aBig data.
650		7	_aCOMPUTERS _xGeneral. _2bisacsh
650		7	_aBig data. _2fast _0(OCoLC)fst01892965
700	1		_aOrhian, Ema.
700	1		_aSasaki, Kai.
700	1		_aYork, Brennon.
856	4	0	_uhttps://doi.org/10.1002/9781119254805 _zWiley Online Library
942			_cEBK
999			_c208700 _d208700