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ShortMe is a url shortening service written in Golang.
It is with high performance and scalable.
ShortMe is ready to be used in production. Have fun with it. :)
Currently, afaik, there are three ways to implement short url service.
Hash
Sample
>>> import random
>>> import string
>>> random.sample('abc', 2)
['c', 'a']
>>> random.sample('abc', 2)
['a', 'b']
>>> random.sample('abc', 2)
['c', 'b']
>>> random.sample('abc', 2)
['a', 'b']
>>> random.sample('abc', 2)
['b', 'c']
>>> random.sample('abc', 2)
['b', 'c']
>>> random.sample('abc', 2)
['c', 'a']
>>>Base
HTTP GET
Expand the short url and return a temporary redirect HTTP status
Example
* Trying 127.0.0.1...
* Connected to 127.0.0.1 (127.0.0.1) port 3030 (#0)
> GET /3 HTTP/1.1
> Host: 127.0.0.1:3030
> User-Agent: curl/7.43.0
> Accept: */*
>
< HTTP/1.1 307 Temporary Redirect
< Location: http://www.google.com
< Date: Fri, 15 Apr 2016 07:25:24 GMT
< Content-Length: 0
< Content-Type: text/plain; charset=utf-8
<
* Connection #0 to host 127.0.0.1 left intactThe web interface mainly used to make url shorting service more intuitively.
For short option, the shorted url, shorted url qr code and the corresponding long page is shown.
For expand option, the expanded url, expanded url qr code and the corresponding expanded page is shown.
Projects that use short-me.
mkdir -p $GOPATH/src/github.com/andyxning
cd $GOPATH/src/github.com/andyxning
git clone https://github.com/andyxning/shortme.git
cd shortme
make buildWe use two databases. Import the two schemas.
[http] # Listen address listen = "0.0.0.0:3030" [sequence_db] # Mysql sequence generator DSN dsn = "sequence:sequence@tcp(127.0.0.1:3306)/sequence" # Mysql connection pool max idle connection max_idle_conns = 4 # Mysql connection pool max open connection max_open_conns = 4 [short_db] # Mysql short service read db DSN read_dsn = "shortme_w:shortme_w@tcp(127.0.0.1:3306)/shortme" # Mysql short service write db DSN write_dsn = "shortme_r:shortme_r@tcp(127.0.0.1:3306)/shortme" # Mysql connection pool max idle connection max_idle_conns = 8 # Mysql connection pool max open connection max_open_conns = 8 [common] # short urls that will be filtered to use black_short_urls = ["version","health","short","expand","css","js","fuck","stupid"] # Base string used to generate short url base_string = "Ds3K9ZNvWmHcakr1oPnxh4qpMEzAye8wX5IdJ2LFujUgtC07lOTb6GYBQViSfR" # Short url service domain name. This is used to filter short url loop. domain_name = "short.me:3030" # Short url service schema: http or https. schema = "http"
We use an Mysql unsigned bigint type to store the sequence counter. According to the Mysql doc we can get 18446744073709551616 different integers. However, according to Golang doc about LastInsertId the returned auto increment integer can only be int64 which will make the sequence smaller than uint64. Even through, we can still get 9223372036854775808 different integers and this will be large enough for most service.
Supposing that we consume 100,000,000 short urls one day, then the sequence counter can last for 2 ** 63 / 100000000 / 365 = 252695124 years.
The max string length needed for encoding 2 ** 63 integers will be 11.
>>> 62 ** 10
839299365868340224
>>> 2 ** 63
9223372036854775808L
>>> 62 ** 11
52036560683837093888LAfter setting up the databases and before running shortme, make sure that the corresponding user and password has been granted. After logging in mysql console, run following sql statement:
In the Flickr blog, Flickr suggests that we can use two databases with one for even sequence and the other one for odd sequence. This will make sequence generator being more available in case one database is down and will also spread the load about generate sequence. After splitting sequence db from one to more, we can use HaProxy as a reverse proxy and thus more sequence databases can be used as one. As for load balance algorithm, i think round robin is good enough for this situation.
In two databases situation, we should add the following configuration to each database configuration file.
auto_increment_offset 1 auto_increment_increment 2
auto_increment_offset 2 auto_increment_increment 2
Then each time to generate a sequence counter, we can execute below sql
statement:
replace into sequence(stub) values("sequence")
In cases we use three databases as sequence counter generator, we should insert a record for each table in two databases.
auto_increment_offset 1 auto_increment_increment 3
auto_increment_offset 2 auto_increment_increment 3
auto_increment_offset 3 auto_increment_increment 3
Then each time to generate a sequence counter, we can execute below sql
statement:
replace into sequence(stub) values("sequence")
Ok, i think you get the point. When using N databases to generate sequence counter, configuration for each database configuration file will just like below:
for i := range N {
add "auto_increment_offset i" to config file
add "auto_increment_increment N" to config file
}
So, sequence generator can be horizontally scalable.
With short urls increasing, many records are stored in one table. This is not an optimal mysql practice. In this case we can simply shard table to bypass this problem.
For example, we can shard according to the base integer using modula hash algorithm. This has a good distribution between tables. We can use 100 short tables with names like short_00/short_01/short_02/.. ./short_99. we can use pseudo code blow to determine which is the table to store the short url record.
baseInteger := sequence.NextSequence()
tableName := fmt.Sprintf("short_%s", baseInteger % 100)
There are many table sharding algorithms, we can shard table according to range id, user name and so on. If we use user name as the criteria to shard table, we can do some aggregate algorithm like how many records a user has created easily. This may also has some drawbacks such as if user Lily and user Lucy are sharded to different tables and Lily shorts about 1k urls Lucy shorts about 1M urls, then we may encounter the unbalance hash problem, i.e., some tables contains more records than others.
In conclusion, there are many factors to consider before we can make a decision which hash algorithm to use.
Sometimes we may want to make some statistics about hit number, UA(User Agent), original IP and so on.
A recommended way to deploy shortme is to use it behind a reverse proxy server such as Nginx. Under this way, the statistics info can be analysed by analysing the access log of Nginx. This is can be accomplished by awk or more trending log analyse stack ELK.
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