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  • U: Anonymous
  • D: 2017-06-07 09:04:33
  • C: Unknown

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ReScene version pyReScene Auto 0.6 PROPAGANDA File size CRC
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56,053
Stored files
27,078 E7787022
3,136 028DB2DC
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003-Hadoop.Platform 0 00000000
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003-Hadoop.Platform\03-Hadoops.storage.gap-Resolving.transactional.access-analytic.performance.tradeoffs.with.Kudu.mp4 [bf05c025b1243aab] 1,575,520,934 A5FBCF11
003-Hadoop.Platform\00-Hadoop.Application.Architectures-Fraud.Detection.Part-1.mp4 [8d5e70e7eaa84a2c] 1,719,982,784 1ED1CEC0
003-Hadoop.Platform\06-From.Oracle.to.Hadoop-Unlocking.Hadoop.for.your.RDBMS.with.Apache.Sqoop.and.other.tools.mp4 [1de931a8f8f5675a] 1,654,084,034 7B88178D
003-Hadoop.Platform\07-Evolving.from.RDBMS.to.NoSQL.plus.SQL.mp4 [4d24d0bde2486efb] 1,461,846,713 A6C6B3D7
003-Hadoop.Platform\01-Hadoop.Application.Architectures-Fraud.Detection.Part-2.mp4 [c4e24d0d491b5ff2] 1,998,278,329 BD5ABA57
003-Hadoop.Platform\04-Designing.an.SQL-on-Hadoop.cluster.using.Impala.simulator-A.use.case.for.the.banking.and.financial.services.sector.mp4 [1f35a35a8843a8fc] 1,288,333,781 04FBE067
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004-IoT.and.Real-time\09-Using.machine.learning.to.identify.fraud.on.Telecom.networks.mp4 [fe589512701e72a] 1,632,849,596 224C7B3B
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004-IoT.and.Real-time\08-Modeling.machine.failure.in.the.IoT.era.mp4 [805856c5b4c37db] 1,464,601,682 0E4E0B90
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004-IoT.and.Real-time\14-How.to.improve.mobile.radio.network.planning.based.on.new.big.data.structure.analysis.mp4 [7875cfd1ce1620e2] 1,705,241,276 41AE9DF3
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006-Hadoop.and.Beyond\02-Architectural.patterns.for.streaming.applications.mp4 [f124a83971f8bcba] 1,506,361,577 247B97C0
007-Design.User_Experience.Visualization 0 00000000
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008-Sponsored 0 00000000
008-Sponsored\02-Analytics.in.action-The.analytics.lifecycle.from.data.discovery.to.deployment.mp4.part 0 00000000
008-Sponsored\00-Patterns.from.the.future.mp4.part 0 00000000
008-Sponsored\01-The.journey.to.value.using.advanced.analytics.mp4.part 0 00000000
Total size: 53,583,051,961
RAR Recovery
Not Present
Labels UNKNOWN
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Execution time: 0.0586 - Memory usage: 0.7MB
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