764 Open source projects that are alternatives of or similar to Weblogsanalysissystem

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深圳地铁大数据客流分析系统🚇🚄🌟

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Big Data Ecosystem Docker

WeDataSphere is a financial level one-stop open-source suitcase for big data platforms. Currently the source code of Scriptis and Linkis has already been released to the open-source community. WeDataSphere, Big Data Made Easy!

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个人学习知识库涉及到数据仓库建模、实时计算、大数据、Java、算法等。

🎯 🌟[大数据面试题]分享自己在网络上收集的大数据相关的面试题以及自己的答案总结.目前包含Hadoop/Hive/Spark/Flink/Hbase/Kafka/Zookeeper框架的面试题知识总结

Open-source distribute workflow schedule tools, also support streaming task.

80+ DevOps & Data CLI Tools - AWS, GCP, GCF Python Cloud Function, Log Anonymizer, Spark, Hadoop, HBase, Hive, Impala, Linux, Docker, Spark Data Converters & Validators (Avro/Parquet/JSON/CSV/INI/XML/YAML), Travis CI, AWS CloudFormation, Elasticsearch, Solr etc.

50+ DockerHub public images for Docker & Kubernetes - Hadoop, Kafka, ZooKeeper, HBase, Cassandra, Solr, SolrCloud, Presto, Apache Drill, Nifi, Spark, Consul, Riak, TeamCity and DevOps tools built on the major Linux distros: Alpine, CentOS, Debian, Fedora, Ubuntu

大数据入门指南 ⭐

A large-scale entity and relation database supporting aggregation of properties

零基础学习spark，大数据学习

Big Data Processing Framework - Unified Data API or SQL on Any Storage

Apache Phoenix / Hbase Spring Boot Microservices

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大数据相关内容汇总，包括分布式存储引擎、分布式计算引擎、数仓建设等。关键词：Hadoop、HBase、ES、Kudu、Hive、Presto、Spark、Flink、Kylin、ClickHouse

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Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learni…

Kylo is a data lake management software platform and framework for enabling scalable enterprise-class data lakes on big data technologies such as Teradata, Apache Spark and/or Hadoop. Kylo is licensed under Apache 2.0. Contributed by Teradata Inc.

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Avro Schema Evolution made easy

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WASP is a framework to build complex real time big data applications. It relies on a kind of Kappa/Lambda architecture mainly leveraging Kafka and Spark. If you need to ingest huge amount of heterogeneous data and analyze them through complex pipelines, this is the framework for you.

low-level helpers for Apache Spark libraries and tests

The Archives Unleashed Toolkit is an open-source toolkit for analyzing web archives.

Docker build project to setup a lightweight hadoop cluster containing hadoop, pig, zookeeper, hbase, phoenix, storm, kafka, kafka manager

Spark、Flink等离线任务的调度以及实时任务的监控

Create clusters of VMs on the cloud and configure them with Ansible.

Data Lineage Tracking And Visualization Solution

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Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax).

Building Large-Scale AI Applications for Distributed Big Data

一个大数据架构师应该掌握的技能

Spark RDD to read, write and delete from HBase

Iceberg is a table format for large, slow-moving tabular data

Generic Data Ingestion & Dispersal Library for Hadoop

MapReduce, Spark, Java, and Scala for Data Algorithms Book

💎🔥大数据学习笔记

编程电子书，电子书，编程书籍，包括C，C#，Docker，Elasticsearch，Git，Hadoop，HeadFirst，Java，Javascript，jvm，Kafka，Linux，Maven，MongoDB，MyBatis，MySQL，Netty，Nginx，Python，RabbitMQ，Redis，Scala，Solr，Spark，Spring，SpringBoot，SpringCloud，TCPIP，Tomcat，Zookeeper，人工智能，大数据类，并发编程，数据库类，数据挖掘，新面试题，架构设计，算法系列，计算机类，设计模式，软件测试，重构优化，等更多分类

Alluxio, data orchestration for analytics and machine learning in the cloud

大数据生态解决方案数据平台：基于大数据、数据平台、微服务、机器学习、商城、自动化运维、DevOps、容器部署平台、数据平台采集、数据平台存储、数据平台计算、数据平台开发、数据平台应用搭建的大数据解决方案。

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Fundamentals of Spark with Python (using PySpark), code examples