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notes.txt
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Pieter Hintjens @hintjens
Browser implementation of #zeromq patterns: https://github.com/progrium/nullmq #nullmq
Expand
7m Pieter Hintjens @hintjens
Node.js implementation of #zeromq patterns: https://github.com/visionmedia/axon … #axon
Expand
++++ The Messaging Layer
So we've solved discovery, presence, connectivity, and simulation. Next on our list: security, unicast messaging, and multicast messaging.
- SASL security
- one-to-one messaging by sending to node
- one-to-many messaging by sending to group
- join group, leave group
- group management across all nodes
++++ File Transfer
Take FILEMQ and plug into this framework.
Notes for The Guide
==1742== Syscall param write(buf) points to uninitialised byte(s)
==1742== at 0x5372100: __write_nocancel (syscall-template.S:82)
==1742== by 0x5306312: _IO_file_write@@GLIBC_2.2.5 (fileops.c:1289)
==1742== by 0x53061D9: new_do_write (fileops.c:543)
==1742== by 0x5307944: _IO_do_write@@GLIBC_2.2.5 (fileops.c:516)
==1742== by 0x5306E6F: _IO_file_close_it@@GLIBC_2.2.5 (fileops.c:170)
==1742== by 0x52FB2CF: fclose@@GLIBC_2.2.5 (iofclose.c:62)
==1742== by 0x4060FF: fmq_file_test (fmq_file.c:342)
==1742== by 0x4021E6: main (fmq_selftest.c:38)
==1742== Address 0x4027000 is not stack'd, malloc'd or (recently) free'd
FILE *handle = fopen ("testdata", "w");
zmq_msg_t msg;
zmq_msg_init_size (&msg, 100);
size_t items = fwrite (zmq_msg_data (&msg), 1, 100, handle);
fclose (handle);
zmq_msg_close (&msg);
+++ Bridging
- why and how
- semantic compatibility
- example 0MQ to HTTP
- using zxxx library?
+++ Decentralised Logging System
- pubsub log events
- filter levels
- capture in log files or memory
- dynamic graphing
- log file cycling
+++ Timer Service
- ticks, 1/10, 1/100, etc.
+++ Disconnected Security
Chapter 9 topics
- the wire level protocol
- a minimal TCP stack
- internals of 0MQ
- generate bindings in
Python
C#
Java
Ruby
++++
0MQ's pipeline pattern (using PUSH and PULL sockets) is reliable to the extent that:
* Workers and collectors don't crash;
* Workers and collectors read their data fast enough to avoid queue overflows.
As with all our reliability patterns, we'll ignore what happens if an upstream node (the ventilator for a pipeline pattern) dies. In practice a ventilator will be the client of another reliability pattern, e.g. Clone.
The Xyz pattern takes pipeline and makes it robust against the only failure we can reasonably handle, namely workers and (less commonly) collectors that crash and lose messages or work.
- assume workers are idempotent
- assume batch size is known in advance (because...)
- assume memory enough to hold full batch
- batch: start (address of collector), tasks, end
- messages numbered 0 upwards inside batch
- assume multiple ventilators for same cluster
- assume collector talks to ventilator, (not same to allow walk-up-and use by ventilators)
- call ventilator the 'client'
- if task missing, resend
- if end of batch missing, resend from last response