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projects
Beyond the
LAMP stack
By Thijs Feryn
PHP
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Hi, I’m Thijs
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I’m
@ThijsFeryn
on Twitter
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I’m an
Evangelist
At
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I’m an
at
Evangelist
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I’m a
at
board member
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LAMP
Stack?
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Linux
Apache
MySQL
PHP
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No content
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✓ ~81% of the web
✓ Easy to learn
✓ Mature (PHP renaissance)
✓ Frameworks & CMS’s
✓ Lots of online resources
✓ THE COMMUNITY
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No content
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➡ Still considered a scripting
language (by some)
➡ Slow(-ish)
➡ Internal variable structure
causes overhead
➡ Everyone can program in PHP,
unfortunately everyone does
➡ Doesn’t scale that well
(without the tricks)
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CPU memory I/O
PHP consumes lots of
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It gets worse “at scale”
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Faster PHP
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✓ Fast
✓ Just In Time compiler
✓ FastCGI support
✓ Drop-in replacement for
PHP-FPM
✓ Hack language
HHVM
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HACK language
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HACK language
$x . $y;
}
function test(): void {
$fn = foo();
echo $fn('baz'); // barbaz
}
Lambdas
!=
closures
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HACK language
{
$x = await \HH\Asio\curl_exec("http://example.com/");
return $x;
}
async function curl_B(): Awaitable {
$y = await \HH\Asio\curl_exec("http://example.net/");
return $y;
}
async function async_curl(): Awaitable {
$start = microtime(true);
list($a, $b) = await \HH\Asio\v(array(curl_A(), curl_B()));
$end = microtime(true);
echo "Total time taken: " . strval($end - $start) . " seconds" .
PHP_EOL;
}
\HH\Asio\join(async_curl());
Async
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What kind of PHP
code do we run?
Why does it slow
down?
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Waiting for DB or API
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HHVM won’t
really speed up
that process.
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Different approach
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Different
tools
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Caching
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Optimize database
Optimize runtime
A
void
A
void
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Don’t
recompute
if the data
hasn’t
changed
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Varnish
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Normally
User Server
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Reverse proxy
User Varnish Server
Proxy
in the data
center
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✓ Varnish Configuration Language
✓ Edge Side Include support
✓ Gzip compression/decompression
✓ Cache purging
✓ HTTP streaming
✓ Grace mode
✓ Configure backends
✓ Backend loadbalancing
✓ ACL protection
✓ VMODs in C
Varnish
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On the request side
✓ Only GET & HEAD
✓ No cookies
✓ No auth headers
On the response side
✓ No “no-cache, no store”
✓ TTL > 0
✓ No set-cookies
When does Varnish cache?
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Extend the
default behavior
in VCL
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vcl 4.0;
sub vcl_recv {
if (req.method != "GET" &&
req.method != "HEAD" &&
req.method != "PUT" &&
req.method != "POST" &&
req.method != "TRACE" &&
req.method != "OPTIONS" &&
req.method != "DELETE") {
/* Non-RFC2616 or CONNECT which is weird. */
return (pipe);
}
if (req.method != "GET" && req.method != "HEAD") {
/* We only deal with GET and HEAD by default */
return (pass);
}
if (req.http.Authorization || req.http.Cookie) {
/* Not cacheable by default */
return (pass);
}
return (hash);
}
Incoming
request
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sub vcl_hash {
hash_data(req.url);
if (req.http.host) {
hash_data(req.http.host);
} else {
hash_data(server.ip);
}
return (lookup);
}
sub vcl_purge {
return (synth(200, "Purged"));
}
Compose
hash key
Evict
cache keys
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sub vcl_hit {
if (obj.ttl >= 0s) {
// A pure unadultered hit, deliver it
return (deliver);
}
if (obj.ttl + obj.grace > 0s) {
// Object is in grace, deliver it
// Automatically triggers a background fetch
return (deliver);
}
// fetch & deliver once we get the result
return (fetch);
}
sub vcl_miss {
return (fetch);
}
sub vcl_deliver {
return (deliver);
}
Deliver
output to
client
Fetch
data from
backend
Or fetch if
it’s stale
Deliver
stored
object
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sub vcl_backend_response {
if (beresp.ttl <= 0s ||
beresp.http.Set-Cookie ||
beresp.http.Surrogate-control ~ "no-store" ||
(!beresp.http.Surrogate-Control &&
beresp.http.Cache-Control ~ "no-cache|no-store|
private") ||
beresp.http.Vary == "*") {
/*
* Mark as "Hit-For-Pass" for the next 2 minutes
*/
set beresp.ttl = 120s;
set beresp.uncacheable = true;
}
return (deliver);
}
Response
from the
backend
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What to extend?
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✓Strip tracking cookies (Google
Analytics, …)
✓Sanitize URL
✓URL whitelist/blacklist
✓PURGE ACLs
✓Edge Side Include rules
✓Alway cache static files
✓Extend hash keys
✓Override TTL
✓Define grace mode
What to extend?
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Caching in your architecture
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Respect HTTP
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Cache-control: public, max-
age=3600, s-maxage=7200
Cache-control: no-cache, no-
store
VS
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Cookies?
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The example
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Don’t cache header
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Cache products for 1 hour
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Cache menus for 1 day
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Edge Side
Includes
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The Demo
{% block content %}{% endblock %}
ESI tags
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The Demo
{{ render_esi(url('nav')) }}
{{ render_esi(url('jumbotron')) }}
{% block content %}{% endblock %}
{{ render_esi(url('footer')) }}
Twig
template in
Silex
ESI or
internal
subrequest
Uses
HttpFragmen
tServiceProv
ider
{{ render_esi(url('footer')) }}
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Or just
use AJAX
Async
Graceful
degradition
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Minimal VCL
Let the
application
handle it
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Where does it fit in?
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✓Cache pages and static assets
✓Fastest way
✓Hit rate may vary
✓Chop your content up in pieces
✓Use ESI or AJAX
✓Gateway to your application
Where does Varnish fit in?
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No content
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✓Cache all images, js, css, wof, …
✓Cache product pages
✓Cache category pages
✓Cache parts of the layout (via ESI)
✓Cache CMS-ish pages
Where does Varnish fit in?
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You can also
host your
static files on
a separate set
of Nginx
servers
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Content Delivery Network
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CDNs are
nothing but a
bunch of
reverse
caching
proxies
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Put the content
where your
user is
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A
voids network saturation
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User specific content
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Keeping track of state
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Cookies
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Stateful
caching
vs
high hit rate
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Not all pages
can be
cached
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Make the data retrieval faster
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Typical MySQL issues
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Data is stored for
flexibility, not for
performance
SQL (joins) allow
different
compositions of the
same data
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Offload the database
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No content
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✓ Key-value store
✓ Fast
✓ Lightweight
✓ Data stored in RAM
✓ ~Memcached
✓ Data types
✓ Data persistance
✓ Replication
✓ Clustering
Redis
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Redis
$ redis-cli
127.0.0.1:6379> ping
PONG
127.0.0.1:6379> set mykey somevalue
OK
127.0.0.1:6379> get mykey
"somevalue
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✓ Strings
✓ Hashes
✓ Lists
✓ Sets
✓ Sorted sets
✓ Geo
✓ …
Redis data types
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Redis
$ redis-cli
127.0.0.1:6379> hset customer_1234 id 1234
(integer) 1
127.0.0.1:6379> hset customer_1234 items_in_cart 2
(integer) 1
127.0.0.1:6379> hmset customer_1234 firstname Thijs lastname
Feryn
OK
127.0.0.1:6379> hgetall customer_1234
1) "id"
2) "1234"
3) "items_in_cart"
4) "2"
5) "firstname"
6) "Thijs"
7) "lastname"
8) "Feryn"
127.0.0.1:6379>
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$ redis-cli
127.0.0.1:6379> lpush products_for_customer_1234 5
(integer) 1
127.0.0.1:6379> lpush products_for_customer_1234 345
(integer) 2
127.0.0.1:6379> lpush products_for_customer_1234 78 12 345
(integer) 5
127.0.0.1:6379> llen products_for_customer_1234
(integer) 5
127.0.0.1:6379> lindex products_for_customer_1234 1
"12"
127.0.0.1:6379> lindex products_for_customer_1234 2
"78"
127.0.0.1:6379> rpop products_for_customer_1234
"5"
127.0.0.1:6379> rpop products_for_customer_1234
"345"
127.0.0.1:6379> rpop products_for_customer_1234
"78"
127.0.0.1:6379> rpop products_for_customer_1234
"12"
127.0.0.1:6379> rpop products_for_customer_1234
"345"
127.0.0.1:6379> rpop products_for_customer_1234
(nil)
127.0.0.1:6379>
Redis
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Predis
https://github.com/nrk/predis
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Clustering
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Where does it fit in?
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✓ Database/API cache
✓ PHP session storage
✓ Message queue (lists)
✓ NoSQL database
✓ Real-time data retrieval
Where does Redis fit in?
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No content
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✓ Stock quantities
✓ Variable pricing
information
✓ Shopping cart
✓ User profile information
Where does Redis fit in?
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Basically:
Real-time
&
volatile data
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BUT:
MySQL can still
remain “source of
truth” database
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No content
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✓Full-text search engine
✓Analytics engine
✓NoSQL database
✓Lucene based
✓Built-in clustering, replication,
sharding
✓RESTful interface
✓Schemaless
ElasticSearch
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{
"name" : "Hijacker",
"cluster_name" : "elasticsearch",
"version" : {
"number" : "2.1.0",
"build_hash" :
"72cd1f1a3eee09505e036106146dc1949dc5dc87",
"build_timestamp" : "2015-11-18T22:40:03Z",
"build_snapshot" : false,
"lucene_version" : "5.3.1"
},
"tagline" : "You Know, for Search"
}
http://localhost:
9200
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POST /my-index
{"acknowledged":true}
POST/my-index/my-type
{
"key" : "value",
"date" : "2015-05-10",
"counter" : 1,
"tags" : ["tag1","tag2","tag3"]
}
{
"_index": "my-index",
"_type": "my-type",
"_id": "AU089olr9oI99a_rK9fi",
"_version": 1,
"created": true
}
Confirmation
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GET/my-index/my-type/AU089olr9oI99a_rK9fi?pretty
{
"_index": "my-index",
"_type": "my-type",
"_id": "AU089olr9oI99a_rK9fi",
"_version": 1,
"found": true,
"_source": {
"key": "value",
"date": "2015-05-10",
"counter": 1,
"tags": [
"tag1",
"tag2",
"tag3"
]
}
}
Retrieve
document by
id
Document &
meta data
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GET /my-index/_mapping?pretty
{
"my-index": {
"mappings": {
"my-type": {
"properties": {
"counter": {
"type": "long"
},
"date": {
"type": "date",
"format": "dateOptionalTime"
},
"key": {
"type": "string"
},
"tags": {
"type": "string"
}
}
}
}
}
}
Schemaless?
Not really …
“Guesses”
mapping on
insert
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POST /products
{
"mappings": {
"product" : {
"_id" : {
"path" : "entity_id"
},
"properties" : {
"entity_id" : {"type" : "integer"},
"name" : {
"type" : "string",
"index" : "not_analyzed",
"fields" : {
"raw" : {
"type" : "string",
"analyzer": "english"
}
}
},
"description" : {
"type" : "string",
"index" : "not_analyzed",
"fields" : {
"raw" : {
"type" : "string",
"analyzer": "english"
}
}
},
"price" : {"type" : "double"},
"sku" : {"type" : "string", "index" : "not_analyzed"},
"created_at" : {"type" : "date", "format" : "YYYY-MM-dd HH:mm:ss"},
"updated_at" : {"type" : "date", "format" : "YYYY-MM-dd HH:mm:ss"} ,
"category" : {
"type" : "string",
"index" : "not_analyzed"
}
}
}
}
}
Explicit
mapping at
index creation
time
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Analyzed
vs
non-analyzed
Full-text
vs
exact value
Filter
vs
Query
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Search
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POST /products/product/_search?pretty
{
"query": {
"match": {
"name.raw": "Linen Blazer"
}
}
}
POST /products/product/_search?pretty
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"term": {
"name": "Linen Blazer"
}
}
}
}
}
Matches
2 products
Matches 1
product
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POST /products/product/_search?pretty
{
"query": {
"filtered": {
"filter": {
"bool": {
"must": [
{
"range": {
"price": {
"gte": 100,
"lte": 400
}
}
}
],
"must_not": [
{
"term": {
"name": "Convertible Dress"
}
}
],
"should": [
{
"term": {
"category": "Women"
}
},
{
"term": {
"category": "New Arrivals"
}
}
]
}
}
}
}
}
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Aggregations
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Group by on steroids
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POST /products/product/_search?pretty
{
"fields": ["category","price","name"],
"query": {
"match": {
"name.raw": "blazer"
}
},
"aggs": {
"avg_price": {
"avg": {
"field": "price"
}
},
"min_price" : {
"min": {
"field": "price"
}
},
"max_price" : {
"max": {
"field": "price"
}
},
"number_of_products_per_category" : {
"terms": {
"field": "category",
"size": 10
}
}
}
}
Multi-group
by
&
query
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"aggregations": {
"min_price": {
"value": 455
},
"number_of_products_per_category": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "Blazers",
"doc_count": 2
},
{
"key": "Default Category",
"doc_count": 2
},
{
"key": "Men",
"doc_count": 2
}
]
},
"max_price": {
"value": 490
},
"avg_price": {
"value": 472.5
}
}
Aggregation
output
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Clustering
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Where does it fit in?
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✓ Full-text search engine
with drill-down search
✓ NoSQL database
✓ Big data analytics tool
using Kibana
Where does ElasticSearch fit in?
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No content
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No content
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✓ All product information
✓ All categories &
attributes
✓ Log archive
✓ Both NoSQL DB & search
engine
Where does ElasticSearch fit in?
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CPU memory I/O
PHP consumes lots of
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Depends on what
you do with it
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✓ Image resizing
✓ Logging/reporting
✓ PDF generation
✓ Check-out on super busy
event sites
✓ …
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Offload the webserver
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Worker scripts
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✓ Uses PHP-CLI
✓ Runs continuously
✓ Process forking
✓ Pthreads
✓ Run worker scripts in
parallel
✓ Managed by supervisord
Worker scripts
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✓ Sync MySQL & Redis
✓ Resize images
✓ Async logging & metrics
✓ Update quantities &
prices
Worker scripts
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Message queues
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No content
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✓ Pub/sub
✓ Speaks AMQP protocol
✓ Supported by Pivotal
✓ Channels/Exchanges/
Queues
✓ Built-in clustering
✓ Reliable messaging
RabbitMQ
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No content
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https://github.com/
videlalvaro/php-amqplib
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channel();
$channel->queue_declare('hello', false, false, false, false);
$msg = new AMQPMessage('Hello World!');
$channel->basic_publish($msg, '', 'hello');
echo " [x] Sent 'Hello World!'\n";
$channel->close();
$connection->close();
Send to
queue
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body, "\n";
};
$connection = new AMQPConnection('127.0.0.1', 5672, 'guest', 'guest');
$channel = $connection->channel();
echo ' [*] Waiting for messages. To exit press CTRL+C', "\n";
$channel->basic_consume('hello', '', false, true, false, false, $callback);
while(count($channel->callbacks)) {
$channel->wait();
}
$channel->close();
$connection->close();
Receive
from
queue
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Where does it fit in?
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✓ Take load away from user
process
✓ Free up resources on
frontend servers
✓ Elaborate messaging
strategies
✓ Async event-based actions
Where do RabbitMQ/workers fit in?
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No content
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✓ Synchronize stock and price
changes between Redis & MySQL
✓ Synchronize product changes
between ElasticSearch & MysQL
✓ Stock/price/sales notifications
✓ Async checkout for busy event
sites
Where do RabbitMQ/workers fit in?
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But with most of
these tools we still
go through the
PHP runtime …
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Other backend
tools to handle
stateful data
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SOA
Microservices
AJAX
Websockets
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No content
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✓ Javascript runtime
✓ Async
✓ Event-driven
✓ Non-blocking I/O
✓ Callbacks
✓ Lightweight
✓ NPM packages
✓ Backend-code in Javascript
NodeJS
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const http = require('http');
const hostname = '127.0.0.1';
const port = 1337;
http.createServer((req, res) => {
res.writeHead(200, { 'Content-Type': 'text/plain' });
res.end('Hello World\n');
}).listen(port, hostname, () => {
console.log(`Server running at http://${hostname}:${port}/`);
});
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ExpressJS
framework for
Node
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var express = require('express');
var app = express();
app.get('/', function (req, res) {
res.send('Hello World!');
});
app.post('/', function (req, res) {
res.send('Got a POST request');
});
app.put('/user', function (req, res) {
res.send('Got a PUT request at /user');
});
app.delete('/user', function (req, res) {
res.send('Got a DELETE request at /user');
});
var server = app.listen(3000, function () {
var host = server.address().address;
var port = server.address().port;
console.log('Example app listening at http://%s:%s', host, port);
});
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Gateway to
ElasticSearch,
RabbitMQ & Redis
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var elasticsearch = require('elasticsearch');
var express = require('express');
var bodyParser = require('body-parser')
var redis = require("redis");
var amqp = require('amqplib/callback_api');
var elasticsearchClient = new elasticsearch.Client({
host: 'localhost:9200',
log: 'error'
});
var redisClient = redis.createClient();
redisClient.on("error", function (err) {
console.log("Error " + err);
});
var app = express();
app.use(bodyParser.urlencoded({ extended: false }))
app.use(bodyParser.json())
Initialize
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app.get('/products', function (req, res) {
elasticsearchClient.search({
index: 'thedemo',
type: 'product',
body: {
query: {
match_all: {}
}
}
}).then(function (resp) {
res.json(resp.hits.hits)
}, function (err) {
console.trace(err.message);
});
});
app.get('/products/:id([0-9]+)/stock', function (req, res) {
redisClient.get(req.params.id+':stock', function(err,
reply) {
res.json(parseInt(reply));
});
});
Get
products
from ES
Get
stock from
Redis
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app.put('/products/:id([0-9]+)/stock', function (req, res) {
var stock = req.body.stock;
var action = req.body.action;
if(action == 'increment') {
redisClient.incrby(req.params.id+':stock',stock, function(err, reply) {
amqp.connect('amqp://localhost', function(err, conn) {
conn.createChannel(function(err, ch) {
ch.assertExchange('stock', 'direct', {durable: false});
ch.publish('stock', 'info', new Buffer(JSON.stringify({id: req.params.id, stock:
parseInt(reply)})));
res.json('Stock for product '+req.params.id+' is now '+parseInt(reply));
});
});
});
} else {
redisClient.decrby(req.params.id+':stock',stock, function(err, reply) {
amqp.connect('amqp://localhost', function(err, conn) {
conn.createChannel(function(err, ch) {
ch.assertExchange('stock', 'direct', {durable: false});
ch.publish('stock', 'info', new Buffer(JSON.stringify({id: req.params.id, stock:
parseInt(reply)})));
res.json('Stock for product '+req.params.id+' is now '+parseInt(reply));
});
});
});
}
});
Update
stock in
Redis
Send
message to
queue
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➜ ~ node node.js
Example app listening at http://:::3000
Running
node.js
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✓ Compiled language for the web
✓ Invented by Google
✓ Strictly typed
✓ Feels like your average
interpreted language
✓ Async features
✓ Built for systems programming
✓ REALLY fast
✓ Not object oriented
Go(lang)
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Where does it fit in?
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Really fast workers
Really fast APIs
Could
replace PHP
workers
Could
replace
NodeJS
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Microservices
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package main
import (
"fmt"
"log"
"github.com/streadway/amqp"
)
func failOnError(err error, msg string) {
if err != nil {
log.Fatalf("%s: %s", msg, err)
panic(fmt.Sprintf("%s: %s", msg, err))
}
}
Initialize
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func main() {
conn, err := amqp.Dial("amqp://guest:guest@localhost:5672/")
failOnError(err, "Failed to connect to RabbitMQ")
defer conn.Close()
ch, err := conn.Channel()
failOnError(err, "Failed to open a channel")
defer ch.Close()
err = ch.ExchangeDeclare(
"stock", // name
"direct", // type
false, // durable
false, // auto-deleted
false, // internal
false, // no-wait
nil, // arguments
)
failOnError(err, "Failed to declare an exchange")
q, err := ch.QueueDeclare(
"", // name
false, // durable
false, // delete when usused
true, // exclusive
false, // no-wait
Runs from
main
function
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conn, err := amqp.Dial("amqp://guest:guest@localhost:5672/")
failOnError(err, "Failed to connect to RabbitMQ")
defer conn.Close()
ch, err := conn.Channel()
failOnError(err, "Failed to open a channel")
defer ch.Close()
err = ch.ExchangeDeclare(
"stock", // name
"direct", // type
false, // durable
false, // auto-deleted
false, // internal
false, // no-wait
nil, // arguments
)
failOnError(err, "Failed to declare an exchange")
Initialize
connection
Initialize
exchange
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q, err := ch.QueueDeclare(
"", // name
false, // durable
false, // delete when usused
true, // exclusive
false, // no-wait
nil, // arguments
)
failOnError(err, "Failed to declare a queue")
err = ch.QueueBind(
q.Name, // queue name
"info", // routing key
"stock", // exchange
false,
nil)
failOnError(err, "Failed to bind a queue")
Declare
queue
Bind to
queue
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msgs, err := ch.Consume(
q.Name, // queue
"", // consumer
true, // auto-ack
false, // exclusive
false, // no-local
false, // no-wait
nil, // args
)
failOnError(err, "Failed to register a consumer")
forever := make(chan bool)
go func() {
for d := range msgs {
log.Printf(" [x] %s", d.Body)
}
}()
log.Printf(" [*] Waiting for messages. To exit press CTRL+C")
<-forever
}
Consume
messages
Async
processing
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The end game
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✓ Cache pages (Varnish)
✓ Assemble content via ESI or AJAX
✓ Static assets on Nginx or CDN
✓ Business logic in lightweight API calls
(NodeJS, Go)
✓ Key-value stores for volatile & real-time
data in Redis
✓ ElasticSearch as a NoSQL database
✓ RabbitMQ for async communication
✓ Worker processes read from message
queue
End game
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Use the right tool
for the job
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Use the tools you like
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