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DTSTART:20230428T200000Z
DTEND:20230428T213000Z
DTSTAMP:20230428T000000Z
SUMMARY:Managing large hierarchical datasets with PyTables
DESCRIPTION:Abstract: \nPyTables is a free and open-source Python library 
 for managing large hierarchical datasets. It is built on top of numpy and 
 the HDF5 scientific dataset library\, and it focuses both on performance 
 and interactive analysis of very large datasets.\nFor large data streams 
 (think multi-dimensional arrays or billions of records) it outperforms 
 databases in terms of speed\, memory usage and I/O bandwidth\, although it 
 is not a replacement to traditional relational databases as PyTables does 
 not support broad relationships between dataset variables.\nPyTables can be 
 even used to organize a workflow with many (thousands to millions) of small 
 files\, as you can create a PyTables database of nodes that can be used 
 like regular opened files in Python. This lets you store a large number of 
 arbitrary files in a PyTables database with on-the-fly compression\, making 
 it very efficient for handling huge amounts of data.\nThis workshop will 
 guide you through the basics with no previous PyTables or HDF5 
 knowledge.\n\nPrerequisites:\nSome basic Python knowledge would be useful\, 
 although many attendees will probably pick it up on the fly\, as we'll try 
 to go slowly.\n\n \n\nPresenter:\nAlex Razoumov earned his Ph.D. in 
 computational astrophysics from the University of British Columbia and held 
 postdoctoral positions in Urbana-Champaign\, San Diego\, Oak Ridge\, and 
 Halifax. He spent five years as HPC Analyst in SHARCNET and in 2014 moved 
 back to Vancouver to focus on scientific visualization and training 
 researchers to use advanced computing tools. Alex is currently based at 
 Simon Fraser University.
LOCATION:Koerner Library
ORGANIZER;CN="Eugene Barsky":MAILTO:eugene.barsky@ubc.ca
CATEGORIES:Data, Research Commons, Research Data Management
CONTACT;CN="Eugene Barsky":MAILTO:eugene.barsky@ubc.ca
STATUS:CONFIRMED
UID:LibCal-3707080
URL:https://libcal.library.ubc.ca/event/3707080
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