Apache Hadoop
GlusterFS
Our great sponsors
Apache Hadoop | GlusterFS | |
---|---|---|
26 | 19 | |
14,255 | 4,451 | |
0.9% | 1.8% | |
9.9 | 6.8 | |
about 18 hours ago | about 18 hours ago | |
Java | C | |
Apache License 2.0 | GNU General Public License v3.0 only |
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 Hadoop
- 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.
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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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In One Minute : Hadoop
GitHub
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.
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How-to-Guide: Contributing to Open Source
Apache Hadoop
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Python vs. Java: Comparing the Pros, Cons, and Use Cases
Hadoop (a Big Data tool).
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Big Data Processing, EMR with Spark and Hadoop | Python, PySpark
Apache Hadoop is an open source framework that is used to efficiently store and process large datasets ranging in size from gigabytes to petabytes of data.Wanna dig more dipper?
GlusterFS
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Tell HN: ZFS silent data corruption bugfix – my research results
https://github.com/gluster/glusterfs/issues/894
And apparently apart from modern coreutils using that, it is mostly gentoo users hitting the bugs in lseek.
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System Design: Netflix
This allows us to fetch the desired quality of the video as per the user's request, and once the media file finishes processing, it will be uploaded to a distributed file storage such as HDFS, GlusterFS, or an object storage such as Amazon S3 for later retrieval during streaming.
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What's the best way to periodically sync two remote servers?
GlusterFS
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System Design: The complete course
But where can we store files at scale? Well, object storage is what we're looking for. Object stores break data files up into pieces called objects. It then stores those objects in a single repository, which can be spread out across multiple networked systems. We can also use distributed file storage such as HDFS or GlusterFS.
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First Apartment and First Homelab
GlusterFS - same as above (https://www.gluster.org/)
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Blocky DNS & synchronizing two instances (primary & secondary DNS)
I'm running three Blocky instances in Docker (and CoreDNS for internal zone resolving) by placing YAML files on a GlusterFS share, so I can update configs on one VM, and then just restart Blocky containers via SSH.
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Why are you not using kubernetes?
Longhorn and storage in general the hardest part of any HA setup, but also not the only choice, at the most basic level something like glusterFS is easy to get running and usable in k8s as NFS volumes, it however doesn't have all the extra features of longhorn.
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HPC design choices
Do you mean https://www.gluster.org/ ?
What are some alternatives?
minio - The Object Store for AI Data Infrastructure
Go IPFS - IPFS implementation in Go [Moved to: https://github.com/ipfs/kubo]
Ceph - Ceph is a distributed object, block, and file storage platform
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]
lizardfs - LizardFS is an Open Source Distributed File System licensed under GPLv3.
Weka
MooseFS - MooseFS – Open Source, Petabyte, Fault-Tolerant, Highly Performing, Scalable Network Distributed File System (Software-Defined Storage)
Tahoe-LAFS - The Tahoe-LAFS decentralized secure filesystem.
GlusterFS - Web Content for gluster.org -- Deprecated as of September 2017
btrfs - Haskell bindings to the btrfs API
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows