Apache Spark聽vs聽TensorFlow

Apache Spark
Apache Spark

1.7K
1.7K
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114
TensorFlow
TensorFlow

1.8K
1.9K
+ 1
72
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Apache Spark vs TensorFlow: What are the differences?

What is Apache Spark? Fast and general engine for large-scale data processing. Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

What is TensorFlow? Open Source Software Library for Machine Intelligence. TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

Apache Spark can be classified as a tool in the "Big Data Tools" category, while TensorFlow is grouped under "Machine Learning Tools".

"Open-source" is the primary reason why developers consider Apache Spark over the competitors, whereas "High Performance" was stated as the key factor in picking TensorFlow.

Apache Spark is an open source tool with 22.5K GitHub stars and 19.4K GitHub forks. Here's a link to Apache Spark's open source repository on GitHub.

According to the StackShare community, Apache Spark has a broader approval, being mentioned in 266 company stacks & 112 developers stacks; compared to TensorFlow, which is listed in 200 company stacks and 135 developer stacks.

Advice on Apache Spark and TensorFlow
Adithya Shetty
Adithya Shetty
Student at PES UNIVERSITY | 5 upvotes 2K views
Needs advice
on
TensorFlowTensorFlow
vs
PyTorchPyTorch
vs
KerasKeras

I have just started learning some basic machine learning concepts. So which of the following frameworks is better to use: Keras / TensorFlow/PyTorch. I have prior knowledge in python(and even pandas), java, js and C. It would be nice if something could point out the advantages of one over the other especially in terms of resources, documentation and flexibility. Also, could someone tell me where to find the right resources or tutorials for the above frameworks? Thanks in advance, hope you are doing well!!

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Pros of Apache Spark
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Cons of Apache Spark
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What is Apache Spark?

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

What is TensorFlow?

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
What companies use Apache Spark?
What companies use TensorFlow?

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What tools integrate with Apache Spark?
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What are some alternatives to Apache Spark and TensorFlow?
Hadoop
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Apache Beam
It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.
Apache Flume
It is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple extensible data model that allows for online analytic application.
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