Search Results for "open office java"
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Showing 912 open source projects for "open office java"
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Java Tablesaw
Java dataframe and visualization library
Tablesaw is a dataframe and visualization library that supports loading, cleaning, transforming, filtering, and summarizing data. If you work with data in Java, it may save you time and effort. Tablesaw also supports descriptive statistics and can be used to prepare data for working with machine learning libraries like Smile, Tribuo, H20.ai, DL4J. Import data from RDBMS, Excel, CSV, TSV, JSON, HTML, or Fixed Width text files, whether they are local or remote (http, S3, etc.) Tablesaw... -
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geometry-api-java
The Esri Geometry API for Java enables developers to write apps
The Esri Geometry API for Java can be used to enable spatial data processing in 3rd-party data-processing solutions. Developers of custom MapReduce-based applications for Hadoop can use this API for spatial processing of data in the Hadoop system. The API is also used by the Hive UDF’s and could be used by developers building geometry functions for 3rd-party applications such as Cassandra, HBase, Storm and many other Java-based “big data” applications. -
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Gephi
Gephi the open graph Viz platform
Gephi is the leading visualization and exploration software for all kinds of graphs and networks. Gephi is open-source and free. Gephi is an award-winning open-source platform for visualizing and manipulating large graphs. It runs on Windows, Mac OS X and Linux. Localization is available in English, French, Spanish, Japanese, Russian, Brazilian Portuguese, Chinese, Czech and German. Fast Powered by a built-in OpenGL engine, Gephi is able to push the envelope with very large networks.... -
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Apache HBase
Get random, realtime read/write access to your Big Data
Use Apache HBase™ when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables, billions of rows X millions of columns, atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable. A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, Apache... -
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JavaParser
Java 1-17 Parser and Abstract Syntax Tree for Java
...While JavaParser generates an Abstract Syntax Tree, JavaSymbolSolver analyzes that AST and is able to find the relation between an element and its declaration (e.g. for a variable name it could be a parameter of a method, providing information about its type, position in the AST, etc). When choosing open source technologies it is important to know your choice will be rewarded by continuous support. The JavaParser community is vibrant and active, with a weekly release cadence that supports language features up to Java 12. -
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Reactor Core
Non-Blocking Reactive Foundation for the JVM
Reactor Core is a foundational library for building reactive applications in Java, providing a powerful API for asynchronous, non-blocking programming. -
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Siddhi Core Libraries
Stream Processing and Complex Event Processing Engine
...Agile development experience with SQL-like query language and graphical drag-and-drop editor supporting event simulation. Lightweight runtime that can natively run on Kubernetes, Docker, VM, or bare metal, and embedded in any Java or Python application. Scalable, and highly available distributed event processing on Kubernetes, with NATS Streaming and Siddhi Kubernetes Operator. -
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Redisson
Valkey & Redis Java client. Real-Time Data Platform
Redisson is a Java client library for Redis that offers distributed data structures, services, and frameworks to build scalable and reliable applications. It simplifies Redis usage by providing in-memory Java objects like maps, sets, locks, queues, and semaphores that are backed by Redis. Redisson supports advanced features like distributed locking, asynchronous APIs, and integrates with frameworks like Spring and Quarkus for reactive and cloud-native development. -
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JavaCall.jl
Call Java from Julia
Call Java programs from Julia. Julia 1.3.0 through Julia 1.6.2 are tested and guaranteed to work on Linux, macOS, and Windows via continuous integration. Julia 1.6.2 and newer should work on Linux and Windows. The JULIA_COPY_STACKS environment variable should be set to 1 on macOS and Linux, but not Windows. -
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OrientDB
DBMS supporting graph, document, full-text and geospatial models
OrientDB is an Open Source Multi-Model NoSQL DBMS with the support of Native Graphs, Documents, Full-Text search, Reactivity, Geo-Spatial and Object Oriented concepts. It's written in Java and it's amazingly fast. No expensive run-time JOINs, connections are managed as persistent pointers between records. You can traverse thousands of records in no time. -
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Elasticsearch
A Distributed RESTful Search Engine
Elasticsearch is a distributed, RESTful search and analytics engine that lets you store, search and analyze with ease at scale. It lets you perform and combine many types of searches; it scales seamlessly, and offers answers incredibly fast with search results you can rank based on a variety of factors. Elasticsearch can be used for a wide variety of use cases, from maps and metrics to site search and workplace search, and with all data types. -
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DataEase
Data visualization analysis tool
An open source data visualization analysis tool available to everyone. DataEase is an open-source data visualization analysis tool that helps users quickly analyze data and gain insight into business trends, so as to achieve business improvement and optimization. DataEase supports rich data source connections, can quickly create charts by dragging and dropping, and can easily share with others. Supports rich chart types (Apache ECharts / AntV), supports drag-and-drop method to quickly create... -
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Apache InLong
Apache InLong - a one-stop integration framework for massive data
Apache InLong is a one-stop integration framework for massive data that provides automatic, secure and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling and other real-time applications based on streaming data. InLong (应龙) is a divine beast in Chinese mythology who guides the river into the sea, and it is regarded as a metaphor of the InLong system for reporting data... -
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Logstash
Centralize, transform and stash your data
Logstash is a server-side data processing pipeline that dynamically ingests data from numerous sources, transforms it, and ships it to your favorite “stash” regardless of format or complexity. It supports and ingests data of all shapes, sizes and sources, dynamically transforms and prepares this data, and transports it to the output of your choice. Logstash is extensible, with over 200 plugins available to let you create and configure your pipeline how you choose. -
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RStudio
RStudio is an integrated development environment (IDE) for R
RStudio is a powerful, full-featured integrated development environment (IDE) tailored primarily for the R programming language but increasingly supportive of other languages like Python and Julia. It brings together console, editor, plotting, workspace, history, and file-management panes into a unified interface, helping data scientists, statisticians, and analysts to work more productively. The IDE is cross-platform: there are desktop versions for Windows, macOS and Linux, as well as a... -
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DQO Data Quality Operations Center
Data Quality Operations Center
DQO is an DataOps friendly data quality monitoring tool with customizable data quality checks and data quality dashboards. DQO comes with around 100 predefined data quality checks which helps you monitor the quality of your data. Table and column-level checks which allows writing your own SQL queries. Daily and monthly date partition testing. Data segmentation by up to 9 different data streams. Build-in scheduling. Calculation of data quality KPIs which can be displayed on multiple built-in... -
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Kestra
Kestra is an infinitely scalable orchestration and scheduling platform
Build reliable workflows, blazingly fast, deploy in just a few clicks. Kestra is an open-source, event-driven orchestrator that simplifies data operations and improves collaboration between engineers and business users. By bringing Infrastructure as Code best practices to data pipelines, Kestra allows you to build reliable workflows and manage them with confidence. Thanks to the declarative YAML interface for defining orchestration logic, everyone who benefits from analytics can participate... -
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Genie
Distributed Big Data Orchestration Service
Genie is a completely open source distributed job orchestration engine developed by Netflix. Genie provides REST-ful APIs to run a variety of big data jobs like Hadoop, Pig, Hive, Spark, Presto, Sqoop and more. It also provides APIs for managing the metadata of many distributed processing clusters and the commands and applications which run on them. -
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Apache Seata
High-performance, open source distributed transaction solution
Seata is a distributed transaction solution for microservices that provides consistent, cross-service commits without forcing every team to adopt the same persistence model. Its architecture separates responsibilities into a global coordinator and per-service participants, so business services remain decoupled while transactions are orchestrated centrally. Multiple modes are supported—AT (automatic, SQL-based with undo logs), TCC (try-confirm-cancel), Saga (long-running compensation), and... -
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Dolphin Scheduler
A distributed and extensible workflow scheduler platform
Apache DolphinScheduler is a distributed and extensible workflow scheduler platform with powerful DAG visual interfaces, dedicated to solving complex job dependencies in the data pipeline and providing various types of jobs available `out of the box`. Dedicated to solving the complex task dependencies in data processing, making the scheduler system out of the box for data processing. Decentralized multi-master and multi-worker, HA is supported by itself, overload processing. All process... -
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Apache Polaris
Apache Polaris, the interoperable, open source catalog
Apache Polaris is an open-source metadata catalog and data management service designed to manage Apache Iceberg tables in modern data lakehouse environments. It provides a centralized catalog that allows multiple compute engines and analytics systems to interact with the same datasets through a standardized interface. By implementing the Iceberg REST catalog API, Polaris enables distributed data platforms to access shared table metadata without tightly coupling storage systems and query... -
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Qualitis
Qualitis is a one-stop data quality management platform
Qualitis is a data quality management platform that supports quality verification, notification, and management for various datasource. It is used to solve various data quality problems caused by data processing. Based on Spring Boot, Qualitis submits quality model task to Linkis platform. It provides functions such as data quality model construction, data quality model execution, data quality verification, reports of data quality generation and so on. At the same time, Qualitis provides... -
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Zingg
Scalable master data management and identity resolution
Zingg is an open-source entity resolution and master data management platform for finding duplicate, related, or matching records across large datasets. It uses machine learning to learn how records should be compared, reducing the need for brittle hand-written matching rules. The project is designed for data engineering and analytics teams working on customer 360, supplier 360, deduplication, fuzzy matching, data quality, and golden record workflows. Zingg runs on Apache Spark and can scale... -
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Apache RocketMQ
Distributed messaging and streaming platform with low latency
Apache RocketMQ is a distributed messaging and streaming platform with low latency, high performance and reliability, trillion-level capacity and flexible scalability. Messaging patterns including publish/subscribe, request/reply and streaming. Financial grade transactional message. Built-in fault tolerance and high availability configuration options base on DLedger. A variety of cross language clients, such as Java, C/C++, Python, Go. Pluggable transport protocols, such as TCP, SSL, AIO.... -
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XGBoost
Scalable and Flexible Gradient Boosting
XGBoost is an optimized distributed gradient boosting library, designed to be scalable, flexible, portable and highly efficient. It supports regression, classification, ranking and user defined objectives, and runs on all major operating systems and cloud platforms. XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems....
