Dataset Count

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Facebook releases StarCraft Max Ai DataSet

Introduction We have just released the largest StarCraft: Brood War Replay DataSet, there are 65,646 games. The complete dataset is compressed with 365 gb,1535 technologists frames, and 496 technologists operation actions. Overview We Release the largest starcraft:brood War replays DataSet verb, with 65646 games. The f ...

Spark: A framework for cluster computing on a workgroup

Translation: Esri Lucas The first paper on the Spark framework published by Matei, from the University of California, AMP Lab, is limited to my English proficiency, so there must be a lot of mistakes in translation, please find the wrong direct contact with me, thanks. (in parentheses, the italic part is my own interpretation) Summary: MapReduce and its various variants, conducted on a commercial cluster on a large scale ...

Spark conversion (transform) and Action (action) list

Spark conversion (transform) and Action (action) list. The following func, most of the time, to make logic clearer, we recommend using anonymous functions! (lambda) "" "Ps:java and Python APIs are the same, names and parameters are unchanged." Transform meaning Map (func) Each INPUT element is exported after a Func function conversion and output an element filter (func) returns the value returned after the Func function evaluates to The input element of true is composed of ...

Distributed parallel programming with Hadoop, part 1th

Hadoop is an open source distributed parallel programming framework that realizes the MapReduce computing model, with the help of Hadoop, programmers can easily write distributed parallel program, run it on computer cluster, and complete the computation of massive data. This paper will introduce the basic concepts of MapReduce computing model, distributed parallel computing, and the installation and deployment of Hadoop and its basic operation methods. Introduction to Hadoop Hadoop is an open-source, distributed, parallel programming framework that can be run on a large scale cluster by ...

The premise of website data analysis

Data quality (Quality) is the basis of validity and accuracy of data analysis conclusion and the most important prerequisite and guarantee.   Data quality assurance (Quality Assurance) is an important part of data Warehouse architecture and an important component of ETL. We usually filter dirty data through data cleansing to ensure the validity and accuracy of the underlying data, and data cleaning is usually the front link of data entry into the Data warehouse, so the data must be ...

Website Data analysis: The premise of analysis-data quality 1

Intermediary transaction http://www.aliyun.com/zixun/aggregation/6858.html ">seo diagnose Taobao guest cloud host technology Hall Data quality (information Quality) Is the basis of the validity and accuracy of the data analysis conclusion and the most important prerequisite and guarantee.  Data quality assurance (Quality Assurance) is an important part of data Warehouse architecture and an important component of ETL. ...

"Graphics" distributed parallel programming with Hadoop (i)

Hadoop is an open source distributed parallel programming framework that realizes the MapReduce computing model, with the help of Hadoop, programmers can easily write distributed parallel program, run it on computer cluster, and complete the computation of massive data. This paper will introduce the basic concepts of MapReduce computing model, distributed parallel computing, and the installation and deployment of Hadoop and its basic operation methods. Introduction to Hadoop Hadoop is an open-source, distributed, parallel programming framework that can run on large clusters.

MapReduce: Simple data processing on Super large cluster

MapReduce: Simple data processing on large cluster

The combination of Spark and Hadoop

Spark can read and write data directly to HDFS and also supports Spark on YARN. Spark runs in the same cluster as MapReduce, shares storage resources and calculations, borrows Hive from the data warehouse Shark implementation, and is almost completely compatible with Hive. Spark's core concepts 1, Resilient Distributed Dataset (RDD) flexible distribution data set RDD is ...

Privacy and machine learning

In machine learning applications, privacy should be considered an ally, not an enemy. With the improvement of technology. Differential privacy is likely to be an effective regularization tool that produces a better behavioral model. For machine learning researchers, even if they don't understand the knowledge of privacy protection, they can protect the training data in machine learning through the PATE framework.

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