RSS feeds fail when you subscribe to multiple feeds covering the same general topic area. Consider Alltop’s coverage of Social Media. There are a lot of great stories provided by a huge number of great blogs, but what is the community currently buzzing about? The Zeitgeist for the vertical is missing. Each blog has it’s own tag cloud, but what about the industry as a whole? I wrote about duplication of stories before in my post about the Social Media News Glut. However, the real problem is with RSS or, more specifically, how the current generation of readers uses RSS. Readers are essentially dumb clients providing lists of content based on a time stamp within the feeds to which the user has subscribed.

Google News, breaks this read and regurgitate mold and provides an aggregation of stories based on their content. However, as a user, you can’t create a list of authoritative blogs you want aggregated into a single feed - the personalization and customization is missing. I want the alltop blogs for Social Media blended with a Google news engine providing all coverage of a topic as a series of news items and related stories. I want to get into the long tail of Social Media coverage. Even at this level, duplication still occurs and so grouping of stories would save me time.

The difference between this and Google News as it exists today, is my ability to provide content areas that I find interesting. So I can mix my Social Media news in with my PHP news to get a news source that’s highly specific to me but without duplication. The technology to do this isn’t new. Twitscoop for example attempts to tame the twitter beast by seeing what emerging trends exist and generating a tag cloud for popular terms. Google Trends does some similar work as well. Since the technology already exists, it seems almost trivial to generate an RSS reader that aggregates similar stories. I suspect an online tool, perhaps even Google PageRank, could provide some level of sorting to determine which blog is more authoritative on a specific topic, providing the best version of a specific story, while including the ability to drill down to each original source if the reader is so inclined.

Google may be heading in this direction already with their News product. Customization in the recommended for and geographic sections is evidence of this. However, I can’t add my list of feeds to the Google news engine.

Today I am working on modification of an FB application to permit installation on “pages” in addition to profiles. Facebook has switched (several months ago) to using 64bit integer values for id’s site wide. In the code I use sprintf to create stored procedure calls and couldn’t figure out why the values the the database weren’t matching up with my expectations… the following code would output 536035818 instead of the much larger 30600806890 value I expected. Clearly this is a 32bit vs 64bit.

$big_int = 30600806890;
$format = "%d";
$new_string = sprintf($format, $big_int);
print $new_string;

Since updating to a fully 64 bit platform and so on really isn’t an option, I needed a work around. I composed a quick test for my value and ran it. The test as you can see, it provides output for each of the valid substitution types in sprintf.

$big_int = 30600806890;
$type = array("%b","%c","%d","%e","%u","%f","%F","%o","%s","%x","%X");
for($i=0;$i<count($type);$i++){
        print $type[$i] . ": " . sprintf($type[$i], $big_int) . "\n";
}

This results with the list below. Obviously floating point numbers and strings are the only way to handle these bigint values. A simple drop in value is of course to swap %s for %d as needed, but you lose some type catching which may cause security issues. Instead, I recommend using %0.0f which will suppress the decimal portion - keeping the int an int - while keeping the numeric type checking intact.

%b: 11111111100110100000111101010
%c: ?
%d: 536035818
%e: 3.06008e+10
%u: 536035818
%f: 30600806890.000000
%F: 30600806890.000000
%o: 3774640752
%s: 30600806890
%x: 1ff341ea
%X: 1FF341EA

Looking at sites and tools like Earth, FreeBase, MediaWiki and DBpedia for inspiration, clarity and vision. Would love to hear about any other sites people have played with that provide wiki like front ends to structured data.

Two widgets, both provided by major companies have some discrepancies in their data and the election hasn’t even started yet! I’m not sure who’s wrong here, Google or Microsoft, but either way someone’s data isn’t accurate. When it comes to something like an election - accuracy is very important. As best I can tell, Hawaii is the last poll to close and from the even hour discrepancy, it seems to me someone didn’t account for daylight savings or a timezone somewhere.

Screen grabs taken at the same time

The live widgets for both companies are below. (more…)

Moving database servers is a nontrivial task that requires planning and forethought. This guide provides some tips for planning a migration of a small to midsize databases, but not yet data-warehousing in the 5Gb - 500Gb size. Of course the process will work for smaller databases, and even larger as well. Ultimately your mileage may vary. Depending on the software you’re running your database on, there may be alternate paths, such as replication, available to you. Spend time researching your options before embarking on this type of backup. They can save time and frustration.

This document will not help with sizing your systems, however, completing the “Prepwork” will get you thinking in the right direction as to what you’ll ultimately need to purchase. I highly recommend reading Refactoring SQL Applications by Stéphane Faroult before buying hardware for capacity reasons alone.

Prepwork

Possibly the most important thing you’ll do during the migration is the preparation work. Spend some time looking at what your moving and where you’re moving to up front, it will cause you to answer some questions earlier than later which results in not making rash decisions in the heat of the moment.

1. Inventory and Audit

It’s time to find all the dirty laundry. User’s with inappropriate access (like ’sa’ or ‘root’) for running queries are obvious examples. While it’s tempting to do all of your house cleaning up front, don’t. Document it all so it can be shopped around your organization.

• Look at your user accounts on the RDBMS. Are all of them still currently used? Can any be removed?
• Take a look at the schemas (databases). Are all of them still necessary? Can any be removed?
• Take a look at the tables within each schema. Make note of large objects, you’ll want to do further investigation on these to ensure they’re really serving their intended purpose.
• Make sure you’re backups are running with the intended frequency (and that they’re actually being generated).
• Understand the underlying sub-system design and architecture you currently have.
• Document the pain points you’re experiencing (assuming this is a capacity based move).
• Pick a downtime window for the cutover and ensure you build in some extra time. The length of your downtime can be estimated using your Soggy run.

Armed with this data, you can begin identifying garbage that doesn’t need to move. An example from my experience is a ColdFusion client storage database running on Microsoft SQL Server. This database holds 2 tables CDATA and CGLOBAL each with ~680K rows. With transactional logs etc, the footprint of the database swelled to 7.5Gb. Let alone for a minute that keeping transactional logs on this table was overkill, we were also making significant changes to the application servers. All of this was irrelevant because of other infrastructure changes that were being made concurrently and the database was able to be dropped. This is a singular example of how some research early on can save time later. Moving chunks of data, to disk or over the wire, still takes time - as does the restoration process.

2. Plan the actual steps required to move

This is a page out of David Allen’s GTD. Obvious right? Backup the data and move it to the new server, restore it… done! Well, sure that’s one way to do it, but make sure you’ve got details hashed out on the “move it” bit. If you’re doing this change in a major metro area at rush hour, you’re opening some huge risks into your timeline. But, forgetting traffic; is it best for your environment and your technology? Can you handle the downtime? Consider the following options when flushing out your plan.

• Replication, if available to you, is an ideal way to minimize the downtime. However, you’ll still need to push all data over the wire (or via disk) at some point to get the new equipment to the correct point in time for the log files to begin replication of data effectively.
• Sending up to 20Gb of binary data over the wire is pretty quick, but after that, it may be faster to consider other options for moving data, including moving data via USB/Firewire/eSATA/(insert your favorite external storage method here) or even a whole server.
• Physical data moving takes time and requires coordination, possibly at a datacenter (or multiple datacenters) and may require access be setup ahead of time.

Write down your execution plan, be optimized… you’ll run against this later to keep the noise out of your head.

When moving a large MySQL database between two geographically separated systems, you’re at the mercy of the public internet. Obviously, finding a time that the throughput for your route is best is ideal, but not always an option. After completing a full backup of an entire MySQL database, I pushed the 75Gb over the wire to the new equipment. That process took nearly 2 hours. Armed with the database footprint from your audit, you can use a download calculator to calculate a best case scenario for the transfer time. Keep in mind network congestion, route traffic and latency could increase this time - and those will all increase with distance.

Spring Cleaning

Grab a baseline of your performance. This is a great way to validate that the new solution will do what you expect it to. It’s always nice to see an increase in performance, but it’s better to have a quantified value of just how much increase you get per dollar spent. If you’ll be doing any re-factoring as part of the spring cleaning, be sure to benchmark after you finish that process again.

Begin your house cleaning list by truncating or dropping unnecessary data, tables and schemas. Clean out all of those old user accounts and get your house in order. Ensure you backup proccess has been generating good files and your ready to use those for a Soggy run.

If all has gone well with your process so far, you may be considering just keeping the equipment you’ve got! But if not, and a move is still in your future… get ready to do a Soggy run - note quite the real thing, but not a “dry” run either, because we want to time our process.

Soggy Run

Make note of the time… and get moving - stick to the script. Should you deviate (in order or adding additional steps) be sure to note it on the script so you’ll be prepared for the final run. Also note time deltas at intervals so you’ll know if somethings taking too long and your window might need to be extended. It’s possible if you’ll be using replication to manage the transfer, that you won’t need to execute this again, but if you do, it’ll be nice to have the actual steps you’ve taken.

• Make your backups
• Begin your plan for transfering the data
• Ensure you’ve got all the tools, scripts, and equipment you need in the right place in the right order.
• Restore the data
• Validate that EVERYTHING worked. Don’t just look at numbers of databases, but spot check a few (if there are too many to check them all) and ensure the data you’re expecting to be there is there!
  If you are using replication, can you start it, does it work. Trying validating a database or two to ensure everything is right - after the migration is no time to realize you’ve missed data.
• Try your environment against the database and ensure it performs as expected, not just from an accuracy standpoint, but from a performance one as well.
• If your not using replication to handle the next steps, drop all databases from your server. The system will need to drop them when you re-create them and this takes time especially for large databases.
• Make note of the final time. Add some padding to it and set that as your downtime window. Doubling it is safest, but 20% may be sufficient.

D-Day

It’s been rehearsed, the pitfalls discovered, and the process documented - it’s now down to simple execution steps. Ensure you have access, either via phone, or in person to people who can assist with the migration should something go wrong. It’s nice to have resources available to call on. Gather necessary materials and get going.

• Make sure you’re well rested. Nothing is worse than trying to make good decisions when extremely tired.
• Begin your planned downtime window with a clear head. Disable the necessary systems and put up any necessary messaging. Now is the time to ensure your data is perfect and not being altered.
• Run the playbook you’ve created…
• Bring the systems back online!
• Once you’re done with the plan - validate that it’s all working and point your apps, users and the world at your newly completed creation.
• Benchmark! Quantify the improvements you’ve made with similar load to what you’d been running before if possible.

The amount of data available of publicly online is astounding. The US Government has done a pretty good job of providing detailed data to it’s citizens on pretty much anything they keep tabs on. The census data immediately comes to mind, but there is much much more if you take the time to look for it. I stumbled across the USASearch.gov search engine while looking for some population data for cities. The search engine is not as accurate as Google unless you know the government lingo for your data, but it’s pretty good. I suspect there’s a data set there somewhere that would enhance any businesses results and the only cost to you is figuring out how it applies to what you do.