Apache Accumulo
Apache Hadoop
| Apache Accumulo | Apache Hadoop | |
|---|---|---|
| 2 | 26 | |
| 1,046 | 14,342 | |
| -0.1% | 0.6% | |
| 9.7 | 9.9 | |
| about 12 hours ago | 1 day ago | |
| Java | Java | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Apache Accumulo
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In One Minute : Hadoop
Accumulo, a sorted, distributed key/value store that provides robust, scalable data storage and retrieval.
- Apache Accumulo – sorted, distributed, robust, scalable key/value store
Apache Hadoop
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Getting thousands of files of output back from a container
Did you check out tools like https://hadoop.apache.org/ ?
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Trying to run hadoop using docker
check out the various dockerfiles bundled with hadoop on GitHub. you can point to them from within docker-compose. they haven't been updated in a couple years tho.
- Unveiling the Analytics Industry in Bangalore
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5 Best Practices For Data Integration To Boost ROI And Efficiency
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka.
- Hadoop or Spark?
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Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS.
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Effortlessly Set Up a Hadoop Multi-Node Cluster on Windows Machines with Our Step-by-Step Guide
A copy of Hadoop installed on each of these machines. You can download Hadoop from the Apache website, or you can use a distribution like Cloudera or Hortonworks.
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In One Minute : Hadoop
The Apache™ Hadoop™ project develops open-source software for reliable, scalable, distributed computing.
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Elon Musk dissolves Twitter's board of directors
So, clearly with your AP CS class and PLC logic knowledge, if you were dumped into a codebase like Hadoop, QT, or TensorFlow you'd be able to quickly and competently analyze what is going on with that code, understand all the libraries used, know the reasons why certain compromises were made, and be able to make suggestions on how to restructure the code in a different way? Because I've been programming for coming up on two decades and unless a system is within the domains that I have experience in, I would not be able to provide any useful information without a massive onboarding timeline, and definitely wouldn't be able to help redesign anything until actually coding within the system for a significant amount of time.
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A peek into Location Data Science at Ola
This requires the use of distributed computation tools such as Spark and Hadoop, Flink and Kafka are used. But for occasional experimentation, Pandas, Geopandas and Dask are some of the commonly used tools.
What are some alternatives?
Presto - The official home of the Presto distributed SQL query engine for big data
Go IPFS - IPFS implementation in Go [Moved to: https://github.com/ipfs/kubo]
beam - Apache Beam is a unified programming model for Batch and Streaming data processing.
Ceph - Ceph is a distributed object, block, and file storage platform
Zeppelin - Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
Seaweed File System - SeaweedFS is a fast distributed storage system for blobs, objects, files, and data lake, for billions of files! Blob store has O(1) disk seek, cloud tiering. Filer supports Cloud Drive, cross-DC active-active replication, Kubernetes, POSIX FUSE mount, S3 API, S3 Gateway, Hadoop, WebDAV, encryption, Erasure Coding. [Moved to: https://github.com/seaweedfs/seaweedfs]
Hazelcast - Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.
Weka
Apache Flink - Apache Flink
MooseFS - MooseFS – Open Source, Petabyte, Fault-Tolerant, Highly Performing, Scalable Network Distributed File System (Software-Defined Storage)
Hazelcast Jet - Distributed Stream and Batch Processing
GlusterFS - Web Content for gluster.org -- Deprecated as of September 2017