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Apache License 2.0 Java and C client, HTTP, FUSE [8] transparent master failover No Reed-Solomon [9] File [10] 2005 IPFS: Go Apache 2.0 or MIT HTTP gateway, FUSE, Go client, Javascript client, command line tool: Yes with IPFS Cluster: Replication [11] Block [12] 2015 [13] JuiceFS: Go Apache License 2.0 POSIX, FUSE, HDFS, S3: Yes Yes Reed ...
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Apache Hadoop (/ h ə ˈ d uː p /) is a collection of open-source software utilities for reliable, scalable, distributed computing.It provides a software framework for distributed storage and processing of big data using the MapReduce programming model.
Hadoop Distributed File System is a distributed file system that handles large data sets running on commodity hardware (Ishengoma, 2013). It is used to scale a single Apache Hadoop cluster to hundreds (and even thousands) of nodes. HDFS is one of the major components of Apache Hadoop, the others being MapReduce and YARN.
Java tool for working with PDF documents. Apache Pig: High-level platform for creating programs that run on Apache Hadoop. Apache Pivot: Platform for building rich web applications in Java or any JVM-compatible language. Apache POI: APIs for manipulating various file formats based upon Microsoft's OLE 2 Compound Document format. Apache Qpid
Tables in HBase can serve as the input and output for MapReduce jobs run in Hadoop, and may be accessed through the Java API but also through REST, Avro or Thrift gateway APIs. HBase is a wide-column store and has been widely adopted because of its lineage with Hadoop and HDFS. HBase runs on top of HDFS and is well-suited for fast read and ...
The Health Resources and Services Administration's National Center for Health Workforce Analysis projects a 10% shortage of RNs in 2026 and 2031, dropping to 9% in 2036, based on a report released ...
Apache Hive is a data warehouse software project. It is built on top of Apache Hadoop for providing data query and analysis. [3] [4] Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.