As of MISP version 2.4.151 we introduced a simpler way to handle background jobs without relying in CakeResque as this library is no longer mantained.
For the time being both background jobs backends will be supported, but we plan to phase out the CakeResque one in a near future.
The new backend requires Supervisor and some extra PHP packages.
This guide is intended for Ubuntu/Debian systems
flatMap, especially if the following operation will result in high memory usage. The flatMap op usually results in a DataFrame with a [much] larger number of rows, yet the number of partitions will remain the same. Thus, if a subsequent op causes a large expansion of memory usage (i.e. converting a DataFrame of indices to a DataFrame of large Vectors), the memory usage per partition may become too high. In this case, it is beneficial to repartition the output of flatMap to a number of partitions that will safely allow for appropriate partition memory sizes, based upon the
| #!/usr/bin/env python | |
| # -*- mode: python; coding: utf-8 -*- | |
| import sys | |
| import os.path | |
| import smtplib | |
| if len(sys.argv) <= 2: | |
| print('Usage:') | |
| print(' $ python ' + sys.argv[0] + ' mailfrom rcptto <emlfile>') | |
| print('') |