BBoxDB streams: scalable processing of multi-dimensional data streams

نویسندگان

چکیده

Abstract BBoxDB Streams is a distributed stream processing system, which allows the handling of multi-dimensional data. Multi-dimensional streams consist n -dimensional elements, such as position data (e.g., two-dimensional positions cars or three-dimensional aircraft). The software an enhancement BBoxDB, key-bounding-box-value store that big supports continuous range queries and spatial joins; point non-point are supported. Operations in performed primarily on bounding boxes With user-defined filters (UDFs), custom formats can be decoded, box-based operations refined UDF decodes performs intersection tests real geometries WKT encoded elements). A unique feature ability to perform joins between elements previously stored For example, dynamic car efficiently joined with static street network.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Scalable Validation of Data Streams

Xu, C. 2016. Scalable Validation of Data Streams. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 1384. 51 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-554-9600-5. In manufacturing industries, sensors are often installed on industrial equipment generating high volumes of data in real-time. For shortening the machine downtime and re...

متن کامل

SPIRE: Scalable Processing of RFID Event Streams

Radio Frequency Identification (RFID) technology is gaining acceptance in an increasing number of applications for tracking and monitoring purposes. While RFID raises the potential to provide unprecedented visibility in various application domains, data management techniques that are capable of handling massive amounts of data generated by large RFID deployments are still lacking. The sheer vol...

متن کامل

Scalable Splitting of Massive Data Streams

Scalable execution of continuous queries over massive data streams often requires splitting input streams into parallel sub-streams over which query operators are executed in parallel. Automatic stream splitting is in general very difficult, as the optimal parallelization may depend on application semantics. To enable application specific stream splitting, we introduce splitstream functions whe...

متن کامل

Processing Distributed Compoud-Data Streams

In the environment of distribute data stream systems, the available communication bandwidth is a bottleneck resource. It is significant to reduce the communication overhead as possible for improving the availability of communication bandwidth with the constraint of the precision of queries. In this paper, we propose a new method for transferring data streams in distributed data stream systems, ...

متن کامل

PADS: Processing Arbitrary Data Streams

Often such streams are high-volume: AT&T’s call-detail stream contains roughly 300 million calls per day requiring approximately 7GBs of storage space. Typically, such stream data arrives “as is” in ad hoc formats with poor documentation. In addition, the data frequently contains errors. The appropriate response to such errors is applicationspecific. Some applications can simply discard unexpec...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Distributed and Parallel Databases

سال: 2022

ISSN: ['0926-8782', '1573-7578']

DOI: https://doi.org/10.1007/s10619-022-07408-8