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BEGIN:VEVENT
DTSTAMP:20211207T055351Z
LOCATION:Second Floor Atrium
DTSTART;TZID=America/Chicago:20211117T083000
DTEND;TZID=America/Chicago:20211117T170000
UID:submissions.supercomputing.org_SC21_sess242_spostu115@linklings.com
SUMMARY:Delving Into the Abyss: A Distributed Decompression System for Ind
 exing Compressed Repositories
DESCRIPTION:ACM Student Research Competition: Graduate Poster, ACM Student
  Research Competition: Undergraduate Poster, Posters\n\nDelving Into the A
 byss: A Distributed Decompression System for Indexing Compressed Repositor
 ies\n\nWong\n\nDiscovery and use of scientific data is dependent on descri
 ptive metadata. Unfortunately, data lakes often contain compressed data, w
 hich are difficult to index and automatically extract metadata from due to
  storage and I/O constraints when inflating and processing recursively com
 pressed data. Here we describe Abyss, a system capable of indexing large a
 mounts of recursively compressed data. Abyss utilizes a function as a serv
 ice architecture to execute decompression and crawling functions across mu
 ltiple compute endpoints, allowing Abyss to index data at scale and overco
 me storage and I/O limitations. Abyss applies methods for predicting a fil
 e’s decompressed size and batching files to remote endpoints to optimize i
 ndexing. We present a prototype implementation of Abyss and demonstrate th
 at it is capable of indexing real world and synthetic compressed data from
  a 9TB institutional repository.\n\nTag: In-Person Only\n\nRegistration Ca
 tegory: Tech Program Reg Pass, Exhibit Hall Only
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