Automounting swap on local SSD’s on Amazon EC2

Many instances on EC2 (AWS) now have local SSD’s attached. The excellent ubuntu 14.04 image boots brilliantly on these and automatically formats and mounts any of the local SSD storage. However when the instance shuts down, reboots or gets migrated these SSD’s go away so you still need to use the persistent EBS storage for most operations.

If you want to enable swap on the box, add the following to /etc/rc.local – it will create a 2gb swap file each boot on the local SSD and mount it:

I’ve not yet figured out what the process is to format/mount these local disks on bootup it may well be easier to add this to them.

Better Database Search Functionality in 4 Simple Steps

As Google and other search engines are so good at predictive search these days users (ie me) get very frustrated at poor search results on websites or input boxes. Something I try to use across my apps is a decent auto-complete search interface however so many websites are very poor at this either matching only the first part of the string or matching any part of the substring. Additionally sometimes they don’t handle differences in case properly, certainly they don’t usually work with different accenting marks or order particularly well (eg search for beyoglu doesn’t usually return results like Beyoğlu). So, here follows a simple suggestion and code design pattern about how to implement this properly in PostgreSQL (Also works in MySQL although the regex matching code is slightly different). You can then have great instant typeahead functionality for example using the excellent AngularJS Bootstrap Typeahead input. I’ve implemented this in Perl/DBIC but it is a pattern that can be easily applied to any language such as Ruby/Rails or NodeJS.

Whilst there are a number of different search options out there that can plug into existing databases such as ElasticSearch, Sphinx or MySQL/Postgres fulltext search these are often fiddly to set up and are more intended for natural fulltext than for simple phrases or keywords which is what I generally aim for. The below method is pretty quick and easy to set up and allows you full control over the rebuilds, stemming, common word removal etc which is especially important for multi-lingual sites. You can also easily switch between database servers without having to totally redo your search functionality using this method.

Step 1: Add Column to Database Tables

Firstly, for any table you wish to search create a searchdata column probably varchar, with the maximum length of the data you’ll want to be searching (eg article title, author etc combined). For example:

Step 2: Create Search Query Normalization Code

Then in your code create two routines to normalize any search text. Here is a (perl) example from my code:

The first function is purely for normalizing the search terms (firstly stripping accents using the excellent Text::Unidecode module, then killing any non-alphanumeric chars, ensuring only one space between words and no spaces beginning or end of the text), the latter function does the same but also removes any common words you don’t want indexed.

Step 3: Set Columns to Auto Update in Your ORM

In your ORM base-class (you are using an Object-Relational Mapper rather than plain SQL right?) create some functions to handle the auto-population of these fields when the rows get updated by your code. For Perl’s DBIx::Class users here’s the code you inject into your DBIC Result base class. The first function, _get_searchdata is the key one that takes a specified list of columns, normalizes them and returns the searchdata field. The other functions are for the manual refresh of the search data in the row, automatically updating search data on update and create respectively:

In any of your tables where you have added a searchdata column create a method that just returns what columns you want to add to searchdata:

Step 4: Search Queries and Ordering

Whenever a row is added or updated now you’ll have the normalized search text added (see below for a script to auto-populate if you have existing data). To do nice searches you can now execute the following SQL (for MySQL replace ~ with REGEXP operator):

This will match the text anywhere. If you want to only match words beginning with this you can use PostgreSQL’s zero-width start-of-word \m operator (in normal regexp language this would be roughly equivalent to \b although that matches beginning and end of words):

If you want to order results whereby those with beginning-of-string matches go first, then the rest are alphabetical you can do something like (note the !~ as false orders before true):

Well that’s a job well done! You can look at using some sort of index in the database to speed this up but to be honest for tables with less than 10k rows that’s probably not worth while. You’ll need to look at the trie type indexes that Postgres has, I don’t believe MySQL is able to index these sorts of searches.

The DBIC code for this last one:

Extra Step: Create a Reindex Script

You’ll also want to write some code to find any tables with searchdata and update them for initial population. Here’s the perl/dbic solution for this again but should be simple enough with any ORM (note the transaction commit per 100 updates which significantly improves performance on all database servers):

How to use mitmproxy to capture https connections

Based on the excellent in-depth guide found here I’ve written a few quick startup notes to myself below:

Philip’s instructions have -i with the nat prerouting rule and because I’m on wireless this was a source of frustration until I noticed. Forwarding is enabled by default on my box as I run some vm’s from time to time, and the box will automatically forward the packets and just pull out the ones on port 443 which are the ones I’m interested in.

Slow http requests with chrome webview

I was developing an app using the excellent Chrome WebView remote debugging (enabled using the following code in the app)

and noticed that when testing against the live server suddenly what should have been a 100ms request was taking 2-5 seconds to return. I looked at the server and thought the load was a bit high so started up more server processes but that didn’t do anything to solve the problem. Finally, when I closed down the inspector window everything went back to normal. I guess the inspector window (network monitor panel at least) was blocking the process waiting for all the data to be transferred over usb. Annoying but an easy fix to close the inspector window.

Android launch intents from commandline

I’ve been trying to integrate android intents with BuradanOraya specifically to test different scheme parsing bits of code. Open up a shell connection (adb shell) to your android device and then trigger the intent focused on a specific application using a command like:

If you don’t specify a package ie

on my android 5 at least it will come up with a chooser of all the different apps that could open the intent.

Massive battery drain on Android 5 with gmail

I’ve seen this reported quite vaguely in some different forums but having experienced the problem a number of times myself I’ve now come up with the easiest solution. Basically once or twice a month my Nexus 4 running stock Android 5.0.1 eats through its battery in about 3 or 4 hours in spite of hardly being used. On the battery usage page it shows the culprit is the gmail application (I don’t actually use gmail but with Android 5 they have merged the email application into gmail).

Previously I would go to the applications page, click on gmail and clear all data, cache, stop the app and then have to reconfigure my accounts. I’ve noticed that simply force-stopping the app several times, then clearing the cache (which is usually very inflated – presently 100mb of data but 200mb of cache, and I’ve seen it as up to 800mb of cache usage before) seems to do the trick and bring battery usage down to normal.