ept

# Parameters:
prob_nodefail = 0.001     # Probability of a single node failing
replication_factor = 3    # Number of copies of each partition (r)
partitions_per_node = 256 # Number of partitions per node
max_nodes = 10000         # Maximum number of nodes to consider

# (n - r)! / n! == r! / (n choose r)
# Intuitively: the fraction of the n! possible permutations of n nodes that
# results in the replicas of one particular partition to be mapped to three
# particular nodes, in a particular order.

codefromthecrypt

I've had many people ask me questions about OpenTracing, often in relation to OpenZipkin. I've seen assertions about how it is vendor neutral and is the lock-in cure. This post is not a sanctioned, polished or otherwise muted view, rather what I personally think about what it is and is not, and what it helps and does not help with. Scroll to the very end if this is too long. Feel free to add a comment if I made any factual mistakes or you just want to add a comment.

So, what is OpenTracing?

OpenTracing is documentation and library interfaces for distributed tracing instrumentation. To be "OpenTracing" requires bundling its interfaces in your work, so that others can use it to time distributed operations with the same library.

So, who is it for?

OpenTracing interfaces are targeted to authors of instrumentation libraries, and those who want to collaborate with traces created by them. Ex something started a trace somewhere and I add a notable event to that trace. Structure logging was recently added to O

michaellihs

tmux Cheat Sheet

Table of Contents

• General Usage
• Shortcuts
• Commands
• Scripting tmux
• Configuring tmux

vmarcinko

import kafka.server.KafkaConfig;
import kafka.server.KafkaServer;

import java.io.File;
import java.io.FileNotFoundException;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import java.util.Properties;

jkreps

Producer

Setup
bin/kafka-topics.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --create --topic test-rep-one --partitions 6 --replication-factor 1
bin/kafka-topics.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --create --topic test --partitions 6 --replication-factor 3

Single thread, no replication

bin/kafka-run-class.sh org.apache.kafka.clients.tools.ProducerPerformance test7 50000000 100 -1 acks=1 bootstrap.servers=esv4-hcl198.grid.linkedin.com:9092 buffer.memory=67108864 batch.size=8196

jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD