| See attatched |
| 2017-10-23T23:05:00.790+0100 [main] INFO org.redisson.Version - Redisson 3.5.4 | |
| 2017-10-23T23:05:06.025+0100 [redisson-netty-1-6] INFO org.redisson.connection.pool.MasterConnectionPool - 10 connections initialized for localhost/127.0.0.1:6379 | |
| 2017-10-23T23:05:06.025+0100 [redisson-netty-1-7] INFO org.redisson.connection.pool.MasterPubSubConnectionPool - 1 connections initialized for localhost/127.0.0.1:6379 | |
| 2017-10-23T23:05:06.056+0100 [main] INFO org.redisson.Version - Redisson 3.5.4 | |
| 2017-10-23T23:05:06.067+0100 [redisson-netty-5-6] INFO org.redisson.connection.pool.MasterConnectionPool - 10 connections initialized for localhost/127.0.0.1:6379 | |
| 2017-10-23T23:05:06.067+0100 [redisson-netty-5-7] INFO org.redisson.connection.pool.MasterPubSubConnectionPool - 1 connections initialized for localhost/127.0.0.1:6379 | |
| 2017-10-23T23:05:06.138+0100 [main] INFO org.redisson.RedissonNode - 8 map reduce worker(s) registered | |
| 2017-10-23T23:05:06.141+0100 [main] INFO org.redisson.RedissonNode - 1 worker(s) for 'MyExecutor' Exe |
| # Let's add a few entries in our stream "mystream". Every entry in a stream is like | |
| # an hash, composed of fields and values, but every entry can have different fields. | |
| # XADD appends a new entry in a stream, and returns an unique ID which is guaranteed | |
| # be incrementing. | |
| # The first part of the ID is the millisecond unixtime during the | |
| # addition (or the time of the last entry in the stream, if greater than the current time). | |
| # The second part of an entry is a 64 bit counter for entries added in the same ms. | |
| 127.0.0.1:6379> XADD mystream name pamela nicknake kill-9 |
Print from 1st to 92th in less than 0.7ms (Intel first generation i7-920 2.66G) This solutions is limited to upto 92th number due to the size of long but very memory efficient while remain high performance.
More sequences results see code below this.
public class Fibonacci {
private static StringBuffer sb = new StringBuffer();
A Live Object can be understood as an enhanced version of standard Java object, of which an instance reference can be shared not only between threads in a single JVM, but can also be shared between different JVMs across different machines. Wikipedia discribes it as:
Live distributed object (also abbreviated as live object) refers to a running instance of a distributed multi-party (or peer-to-peer) protocol, viewed from the object-oriented perspective, as an entity that has a distinct identity, may encapsulate internal state and threads of execution, and that exhibits a well-defined externally visible behavior.
Redisson Live Object (RLO) realised this idea by mapping all the fields inside a Java class to a redis hash through a runtime-constructed proxy class. All the get/set methods of each field are translated to hget/hset commands operated on the redis hash, making it accessable to/from any clients connected to the same redis server. As we a
| ### Start HTTP ### | |
| # Enter rule | |
| -A ufw-before-input -p tcp --dport 80 -j ufw-http | |
| -A ufw-before-input -p tcp --dport 443 -j ufw-http | |
| # Limit connections per Class C | |
| -A ufw-http -p tcp --syn -m connlimit --connlimit-above 50 --connlimit-mask 24 -j ufw-http-logdrop | |
| # Limit connections per IP |
| #!/bin/sh | |
| grep 11/Jul/2015 access_log | grep "POST /wp-login.php" | awk '{ print $1 }' | sort -n | uniq -c | sort -rn | grep "\\([1-9][0-9][0-9][0-9]\\+\\) " | awk '{ print $2 }' | xargs -n 1 ufw insert 1 deny from | |
| # or change the grep criteria to suit your need. |