Sentence examples for batch data processing from inspiring English sources

An interesting open-source project for distributed stream and batch data processing, Apache Flink, has collated a library of publicly available ML algorithms that will scale to large data sets.

The specific technologies might differ from place to place, but every large web company has some sort of architecture in place for handling real-time, near-real-time and batch data processing.

While statistical functions, batch data processing, and fitting functions are generally intuitive, the quality, diversity, and ease of plotting publication quality figures in Origin matches or surpasses other data analysis and graphing software packages.

To facilitate batch data processing, a coding program based on this 6-step procedure was created with MS-Excel so that the −log[p] score for various peptide:MHC features could be calculated and reported equivalently (Figure 2B).

MapReduce is designed for batch parallel data processing such as log analysis and text processing.

While the iterative batch approach to data processing improves on many of the deficiencies of the MapReduce paradigm, it still does not offer the ability to process data in real-time.

Furthermore, FC-NIRS can accomplish batch processing during data processing and analysis, thereby greatly reducing the time cost of addressing a large number of datasets.

SQLstream's new 2.0 technology allows companies to reduce the time required to turn data into readable information by capturing and reading the data in live streams (using SQL language) versus batch-techniques of data processing, which is reading and interpreting in chunks after it hits databases.

Data processing modes Batch, real and hybrid processing Data security Security compliance according to the platform requirements.

QPLOT also tries to improve packages designed specifically for handling aligned data (such as SAMStat [ 11] and Picard [ 12]) through its computational efficiency (QPLOT can sample regions of the genome randomly so as to rapidly evaluate very large alignments) and its ability to handle many samples (which helps to identify batch effects and other transient data processing problems).

Cheng et al. [ 16] also utilized the ATC classification as the benchmark to compare similarity metrics using two data processing methods: the batch DMSO control and the mean centering normalization.