hashFS: Applying Hashing to Optimize File Systems for Small File Reads

2010 ◽  
Author(s):  
Paul Lensing ◽  
Dirk Meister ◽  
André Brinkmann
Keyword(s):  
File Systems ◽  
Small File

Small-file access in parallel file systems

2009 ◽  
Author(s):  
Philip Carns ◽  
Sam Lang ◽  
Robert Ross ◽  
Murali Vilayannur ◽  
Julian Kunkel ◽  
...  
Keyword(s):  
File Systems ◽  
Parallel File Systems ◽  
File Access ◽  
Parallel File ◽  
Small File

scholarly journals solution for the future: small file management by optimizing Hadoop

2018 ◽  
Vol 7 (2.6) ◽  
pp. 221
Author(s):  
O Achandair ◽  
S Bourekkadi ◽  
E Elmahouti ◽  
S Khoulji ◽  
M L. Kerkeb
Keyword(s):  
Low Cost ◽  
Random Access ◽  
File Systems ◽  
Map Reduce ◽  
Second Phase ◽  
Distributed File Systems ◽  
New Strategy ◽  
Hadoop Distributed File System ◽  
Processing Component ◽  
Small File

Hadoop Distributed File System (HDFS) is designed to reliably store very large files across machines in a large cluster. It is one of the most used distributed file systems and offer a high availability and scalability on low-cost hardware. All Hadoopframework have HDFS as their storage component. Coupled with map reduce, which is the processing component, HDFS and Map Reduce (a processing component) have become the standard platforms for any management of big data in these days. HDFS however, in terms of design has the ability to handle huge numbers of large files,  but when it comes to its deployments to handle large amounts of small files it might not be very effective. This paper puts forward a new strategy of managing small files. The approach will consists of two principal phases. The first phase will deal with the consolidating of aaclients input files, storing it continuously in a particular allocated block, that is a SequenceFile format, and so on into the next blocks. In this way we avoid the use of multiple block allocations for different streams, this reduces calls for available blocks and also reduces the metadata memory on the NameNode. Note the reason for this is that groups of small files packaged in a SequenceFile on the same block require one entry instead of one of each small file. The second phase will involve analyzing the attributes of stored small files so they can be distributed them in a way that the most called files will be referenced by an additional index as a MapFile format to reduce the read throughput during random access. 

scholarly journals Impact on Quality of Life of Patients Treated by Different File Systems for Root Canal Treatment

2021 ◽  
Author(s):  
L.S. Priyanka ◽  
Lakshmi Nidhi Rao ◽  
Aditya Shetty ◽  
Mithra N. Hegde ◽  
Chitharanjan Shetty
Keyword(s):  
Quality Of Life ◽  
Oral Health ◽  
Postoperative Pain ◽  
Root Canal ◽  
File Systems ◽  
Study Groups ◽  
Significant Difference ◽  
Related Quality ◽  
The Impact

Abstract Introduction The outcomes of oral health conditions and therapy for those conditions are described by the term “oral health-related quality of life.” Oral health-related quality of life is recognized by the World Health Organization as an important part of the Global Oral Health Program. The study aims to compare the impact of three root canal preparation systems on patients’ quality of life and correlate postoperative pain with the impact on the quality of life. Materials and Methods A survey was performed in which 90 patients were randomly assigned to three groups based on the root canal preparation system: (1) ProTaper Gold (Dentsply, Tulsa Dental Specialties, Tulsa, Oklahoma, United States), (2) Neoendo flex (Neoendo, India),and (3) Hyflex EDM/CM (Coltene Whaledent) that included 30 participants in each group. Data collection included the implementation of a demographic data questionnaire, Oral Health Impact Profile 14 (quality of life), and visual analogue scale(pain). The questionnaire was given after root canal treatment in the first 24 hours. The data obtained were statistically analyzed. Results No significant differences were found in the quality of life among study groups. Group 1 demonstrated a highly significant difference in the postoperative pain with p value of 2.67. Conclusion Within the limitations of the present study, Protaper Gold showed a highly significant difference in postoperative pain when compared with other file systems. No significant differences were found in the quality of life among the study groups.

FILT: Optimizing KV-Embedded File Systems through Flat Indexing

2020 ◽  
Author(s):  
Chen Chen ◽  
Tongliang Deng ◽  
Jian Zhang ◽  
Yanliang Zou ◽  
Xiaomin Zhu ◽  
...  
Keyword(s):  
File Systems

Distributed Hierarchical File Systems strike back in the Cloud

2020 ◽  
Author(s):  
Mahmoud Ismail ◽  
Salman Niazi ◽  
Mauritz Sundell ◽  
Mikael Ronstrom ◽  
Seif Haridi ◽  
...  
Keyword(s):  
File Systems

Technical Perspective: Proving file systems meet expectations

2017 ◽  
Vol 60 (4) ◽  
pp. 74-74
Author(s):  
Gernot Heiser
Keyword(s):  
File Systems

File systems deserve verification too!

2014 ◽  
Vol 48 (1) ◽  
pp. 58-64 ◽  
Author(s):  
Gabriele Keller ◽  
Toby Murray ◽  
Sidney Amani ◽  
Liam O'Connor ◽  
Zilin Chen ◽  
...  
Keyword(s):  
File Systems

scholarly journals Realistic and Scalable Benchmarking Cloud File Systems: Practices and Lessons from AliCloud

2017 ◽  
Vol 28 (11) ◽  
pp. 3272-3285 ◽  
Author(s):  
Zujie Ren ◽  
Weisong Shi ◽  
Jian Wan ◽  
Feng Cao ◽  
Jiangbin Lin
Keyword(s):  
File Systems
Sign in / Sign up

Export Citation Format

Share Document