Tag: Recently Read

In the very early days of Percona Vadim wrote very nice post about GROUP_CONCAT.But I want to show you a bit more about it.When is GROUP_CONCAT useful? Usually while working with Support customers I recommend it when you have aggregation of many-to-many info. It makes the view simpler and more beautiful and it doesn’t need much effort to make it work.Some simple examples:This is a test table:CREATE TABLE `group_c` (
`parent_id` int(11) DEFAULT NULL,
`child_id` int(11) DEFAULT NULL
) ENGINE=InnoDB;
INSERT INTO group_c(parent_id, child_id)
VALUES (1,1),(1,2),(1,3),(2,1),(2,4),(1,4),(2,6),(3,1),(3,2),(4,1),(4,1),(1,1),(5,0);Without grouping info the only way you can check things is:mysql> SELECT DISTINCT
-> parent_id, child_id
-> FROM group_c
-> ORDER BY parent_id;
+———–+———-+
| parent_id | child_id |
+———–+———-+
| 1 | 1 |
| 1 | 2 |
| 1 | 3 |
| 1 | 4 |
| 2 | 1 |
| 2 | 3 |
| 2 | 4 |
| 2 | 6 |
| 3 | 1 |
| 3 | 2 |
| 4 | 1 |
| 5 | 0 |
+———–+———-+
12 rows in set (0.00 sec)But it looks much better and easier to read with GROUP_CONCAT:mysql> SELECT DISTINCT
-> parent_id, GROUP_CONCAT(DISTINCT child_id ORDER BY child_id) AS child_id_list
-> FROM group_c
-> group by parent_id
-> ORDER BY parent_id;
+———–+—————+
| parent_id | child_id_list |
+———–+—————+
| 1 | 1,2,3,4 |
| 2 | 1,3,4,6 |
| 3 | 1,2 |
| 4 | 1 |
| 5 | 0 |
+———–+—————+
5 rows in set (0.00 sec)Easy? Let’s go to production usage and some “real” examples Assume you have 4 Support Engineers who were working with 6 Customers this week on 15 issues.As it usually happens: everyone (sure, except those who are on vacation ) worked on everything with everybody.How you would represent it?Here is my way:Create test tables:engineers (id, name, surname, URL) – list of engineerscustomers (id, company name, URL) – list of customersissues (id, customer_id, description) – list of issues assigned to customersworkflow (id, engineer_id, issue_id) – list of actions: issues and engineers who worked on them– Engineers
CREATE TABLE engineers (
id SMALLINT UNSIGNED NOT NULL AUTO_INCREMENT,
e_name VARCHAR(30) NOT NULL,
e_surname VARCHAR(30) NOT NULL,
url VARCHAR(255) NOT NULL,
PRIMARY KEY (id)
) ENGINE=InnoDB;
— Customers
CREATE TABLE customers (
id SMALLINT UNSIGNED NOT NULL AUTO_INCREMENT,
company_name VARCHAR(30) NOT NULL,
url VARCHAR(255) NOT NULL,
PRIMARY KEY (id)
) ENGINE=InnoDB;
— Issues (Issue-Customer)
CREATE TABLE issues (
id MEDIUMINT UNSIGNED NOT NULL AUTO_INCREMENT,
customer_id VARCHAR(30) NOT NULL,
description TEXT,
PRIMARY KEY (id)
) ENGINE=InnoDB;
— Workflow (Action: Engineer-Issue(Customer))
CREATE TABLE workflow (
action_id INT UNSIGNED NOT NULL AUTO_INCREMENT,
engineer_id SMALLINT UNSIGNED NOT NULL,
issue_id SMALLINT UNSIGNED NOT NULL,
PRIMARY KEY (action_id)
) ENGINE=InnoDB;
INSERT INTO engineers (e_name, e_surname, url)
VALUES
(‘Miguel’, ‘Nieto’, ‘http://www.percona.com/about-us/our-team/miguel-angel-nieto’),
(‘Marcos’, ‘Albe’, ‘http://www.percona.com/about-us/our-team/marcos-albe’),
(‘Valerii’, ‘Kravchuk’, ‘http://www.percona.com/about-us/our-team/valerii-kravchuk’),
(‘Michael’, ‘Rikmas’, ‘http://www.percona.com/about-us/our-team/michael-rikmas’);
INSERT INTO customers (company_name, url)
VALUES
(‘OT’,’http://www.ovaistariq.net/’),
(‘PZ’,’http://www.peterzaitsev.com/’),
(‘VK’,’http://mysqlentomologist.blogspot.com/’),
(‘FD’,’http://www.lefred.be/’),
(‘AS’,’http://mysqlunlimited.blogspot.com/’),
(‘SS’,’https://www.flamingspork.com/blog/’);
INSERT INTO issues(customer_id, description)
VALUES
(1,’Fix replication’),
(2,’Help with installation of Percona Cluster’),
(3,’Hardware suggestions’),
(4,’Error: no space left’),
(5,’Help with setup daily backup by Xtrabackup’),
(6,’Poke sales about Support agreement renewal’),
(4,’Add more accounts for customer’),
(2,’Create Hot Fix of Bug 1040735′),
(1,’Query optimisation’),
(1,’Prepare custom build for Solaris’),
(2,’explain about Percona Monitoring plugins’),
(6,’Prepare access for customer servers for future work’),
(5,’Decribe load balancing for pt-online-schema-change’),
(4,’Managing deadlocks’),
(1,’Suggestions about buffer pool size’);
INSERT INTO workflow (engineer_id, issue_id)
VALUES (1,1),(4,2),(2,3),(1,4),(3,5),(2,6),(3,7),(2,8),(2,9),(1,10),(3,11),(2,12),(2,13),(3,14),(1,15),(1,9),(4,14),(2,9),(1,15),(3,10),(4,2),(2,15),(4,8),(4,4),(3,11),(1,7),(3,7),(1,1),(1,9),(3,4),(4,3),(1,5),(1,7),(1,4),(2,4),(2,5);Examples:List of issues for each engineer (GROUP_CONCAT):mysql> SELECT
-> CONCAT (e_name, ‘ ‘, e_surname) AS engineer,
-> GROUP_CONCAT(DISTINCT issue_id, ‘ (‘, c.company_name,’)’ ORDER BY issue_id SEPARATOR ‘, ‘ ) AS ‘issue (customer)’
-> FROM
-> workflow w,
-> engineers e,
-> customers c,
-> issues i
-> WHERE
-> w.engineer_id = e.id
-> AND w.issue_id = i.id
-> AND i.customer_id = c.id
-> GROUP BY
-> e.id
-> ORDER BY
-> e_name, e_surname;
+——————+—————————————————————————+
| engineer | issue (customer) |
+——————+—————————————————————————+
| Marcos Albe | 3 (VK), 4 (FD), 5 (AS), 6 (SS), 8 (PZ), 9 (OT), 12 (SS), 13 (AS), 15 (OT) |
| Michael Rikmas | 2 (PZ), 3 (VK), 4 (FD), 8 (PZ), 14 (FD) |
| Miguel Nieto | 1 (OT), 4 (FD), 5 (AS), 7 (FD), 9 (OT), 10 (OT), 15 (OT) |
| Valerii Kravchuk | 4 (FD), 5 (AS), 7 (FD), 10 (OT), 11 (PZ), 14 (FD) |
+——————+—————————————————————————+
4 rows in set (0.00 sec)List of engineers for each customer (GROUP_CONCAT inside of GROUP_CONCAT):mysql> SELECT
-> c.company_name AS company,
-> GROUP_CONCAT(DISTINCT issue_id, ‘ (‘, engineer_list, ‘)’ ORDER BY issue_id SEPARATOR ‘, ‘ ) AS issue
-> FROM
-> workflow w,
-> engineers e,
-> customers c,
-> issues i,
-> (SELECT
-> i.id AS i_id,
-> GROUP_CONCAT(DISTINCT CONCAT(e_name, ‘ ‘, e_surname) ORDER BY e_name SEPARATOR ‘, ‘) AS engineer_list
-> FROM
-> workflow w,
-> engineers e,
-> issues i
-> WHERE
-> w.engineer_id = e.id
-> AND w.issue_id = i.id
-> GROUP BY
-> i.id) AS e_list
-> WHERE
-> w.engineer_id = e.id
-> AND w.issue_id = i.id
-> AND i.customer_id = c.id
-> AND w.issue_id = e_list.i_id
-> GROUP BY
-> c.id
-> ORDER BY
-> c.company_name;
+———+——————————————————————————————————————————————–+
| company | issue (engineer) |
+———+——————————————————————————————————————————————–+
| AS | 5 (Marcos Albe, Miguel Nieto, Valerii Kravchuk), 13 (Marcos Albe) |
| FD | 4 (Marcos Albe, Michael Rikmas, Miguel Nieto, Valerii Kravchuk), 7 (Miguel Nieto, Valerii Kravchuk), 14 (Michael Rikmas, Valerii Kravchuk) |
| OT | 1 (Miguel Nieto), 9 (Marcos Albe, Miguel Nieto), 10 (Miguel Nieto, Valerii Kravchuk), 15 (Marcos Albe, Miguel Nieto) |
| PZ | 2 (Michael Rikmas), 8 (Marcos Albe, Michael Rikmas), 11 (Valerii Kravchuk) |
| SS | 6 (Marcos Albe), 12 (Marcos Albe) |
| VK | 3 (Marcos Albe, Michael Rikmas) |
+———+——————————————————————————————————————————————–+
6 rows in set (0.00 sec)PHP/HTML? Why not? It’s easy Source Code:’, CONCAT(c.company_name), ” ORDER BY e_name SEPARATOR ‘, ‘) AS company,
i.description,
GROUP_CONCAT(DISTINCT ”, CONCAT(e_name, ‘ ‘, e_surname), ” ORDER BY e_name SEPARATOR ‘, ‘) AS engineer_list
FROM
workflow w,
engineers e,
customers c,
issues i
WHERE
w.engineer_id = e.id
AND w.issue_id = i.id
AND i.customer_id = c.id
GROUP BY
i.id
ORDER BY
i.id";
$result = $mysqli->query($query);
while($row = $result->fetch_array())
{
$rows[] = $row;
}
echo "";
foreach($rows as $row)
{
echo "’;
}
echo "“.$row["id"].’‘.$row["company"].’‘.$row["description"].’‘.$row["engineer_list"].’";
$result->close();
$mysqli->close();
?>Result:1OTFix replicationMiguel Nieto2PZHelp with installation of Percona ClusterMichael Rikmas3VKHardware suggestionsMarcos Albe, Michael Rikmas4FDError: no space leftMarcos Albe, Michael Rikmas, Miguel Nieto, Valerii Kravchuk5ASHelp with setup daily backup by XtrabackupMarcos Albe, Miguel Nieto, Valerii Kravchuk6SSPoke sales about Support agreement renewalMarcos Albe7FDAdd more accounts for customerMiguel Nieto, Valerii Kravchuk8PZCreate Hot Fix of Bug 1040735Marcos Albe, Michael Rikmas9OTQuery optimisationMarcos Albe, Miguel Nieto10OTPrepare custom build for SolarisMiguel Nieto, Valerii Kravchuk11PZexplain about Percona Monitoring pluginsValerii Kravchuk12SSPrepare access for customer servers for future workMarcos Albe13ASDecribe load balancing for pt-online-schema-changeMarcos Albe14FDManaging deadlocksMichael Rikmas, Valerii Kravchuk15OTSuggestions about buffer pool sizeMarcos Albe, Miguel NietoThat’s a power of GROUP_CONCAT!The post The power of MySQL’s GROUP_CONCAT appeared first on MySQL Performance Blog.
via Planet MySQL
The power of MySQL’s GROUP_CONCAT

WASHINGTON—Responding to widespread criticism regarding its health care website, the federal government today unveiled its new, improved Obamacare program, which allows Americans to purchase health insurance after installing a software bundle contai…

via The Onion
New, Improved Obamacare Program Released On 35 Floppy Disks

Geo-enabled (or location enabled) applications are very common nowadays and many of them use MySQL. The common tasks for such applications are:Find all points of interests (i.e. coffee shops) around (i.e. a 10 mile radius) the given location (latitude and longitude). For example we want to show this to a user of the mobile application when we know his/her approximate location. (This usually means we need to calculate a distance between 2 points on Earth).Find a ZIP code (U.S. Postal address) for the given location or determine if this location is within the given area. Another example is to find a school district for the given property.MySQL had the spatial functions originally (implementation follows a subset of OpenGIS standard). However, there are 2 major limitation of MySQL spatial functions that can make it difficult to use those functions in geo-enabled applications:Distance between 2 points.  The “distance” function was not implemented before MySQL 5.6. In addition (even in MySQL 5.6), all calculations (e.g. distance between 2 points) are done using a planar coordinate system (Euclidean geometry). For the distance between 2 points on Earth this can produce incorrect results.Determine if the point is inside a polygon. Before MySQL 5.6 the functions that test the spatial relationships between 2 geometries (i.e. find if the given point is within a polygon) only used a Minimum Bounding Rectangle (MBR). This is a major limitation for example #2 above (I will explain it below).In my old presentation for the 2006 MySQL User Conference I  showed how to calculate distances on Earth in MySQL without using the MySQL spatial functions. In short, one can store the latitude and longitude coordinates directly in MySQL fields (decimal) and use a haversine  formula to calculate distance.New MySQL 5.6 Geo Spatial Functions The good news is:1) MySQL 5.6 adds a set of new functions (some of them are not 100% documented though) that use the object shapes rather than the MBR to calculate spatial relationships. Those new functions begins with “ST_”, i.e.contains(g1, g2)  uses MBR only (not exact!)st_contains(g1, g2) uses exact shapes2) MySQL 5.6 implements st_distance(g1, g2) function that calculates the distance between 2 geometries, which is currently not documented (I’ve filed the feature request to document the st_distance function in MySQL)The bad news is:1) All functions still only use the planar system coordinates. Different SRIDs are not supported.2) Spatial indexes (RTREE) are only supported for MyISAM tables. One can use the functions for InnoDB tables, but it will not use spatial keys.Example of MySQL’s MBR “false positives”To illustrate why we do not want to use MBR-based functions for geospatial search, I’ve generated 2 polygons that represent 2 zip code boundaries in San Francisco, CA and placed it on Google Maps.The blue rectangle represents the Minimum Bounding Rectangle of Zip code “91102″ (I’ve used envelope() mysql function to obtain coordinates for the MBR). As we can see it covers both zip code 94103 and 94102. In this case if we have coordinates of a building in the city’s “south of market” district (ZIP 91103) and try to find a zip code it belongs to using the “contains()” function we will have a “false positives”:mysql> select zip from postalcodes where contains(geom, point(-122.409153, 37.77765));
+——-+
| zip |
+——-+
| 94102 |
| 94103 |
| 94158 |
+——-+
3 rows in set (0.00 sec)In this particular example we got 3 zip codes as the MBR of 94158 also overlaps this area. Another point in “south of market” can actually produce 4 different zip codes. However, in MySQL 5.6 we can use the new st_contains function:mysql> select zip from postalcodes where st_contains(geom, point(-122.409153, 37.77765));
+——-+
| zip |
+——-+
| 94103 |
+——-+
1 row in set (0.00 sec)As we can see st_contains() produces the correct results.Find a ZIP code for the given locationStarting with MySQL 5.6 one can use the MySQL spatial functions st_contains or st_within to find if the given point is inside the given polygon. In our scenario we will need to find the zip code for the given latitude and longitude. To do that in MySQL we can perform the following steps:Load the zip code boundaries into MySQL as a multipoligon. There are a number of ways to get this done, one way is to download the shape files from the Census website and convert them to MySQL using org2org utility. (I will describe this in more detail in upcoming blog posts). The data will be stored as MySQL Geometry object, to convert it to text we can use astext(geom) function.Use the st_contains() or st_within() functions:mysql> select zip from postalcodes where st_contains(geom, point(-122.409153, 37.77765));
+——-+
| zip |
+——-+
| 94103 |
+——-+
1 row in set (0.00 sec) ormysql> select zip from postalcodes where st_within(point(-122.409153, 37.77765), geom);
+——-+
| zip |
+——-+
| 94103 |
+——-+
1 row in set (0.00 sec)Spatial Index for “ST_” functionsMyISAM tables support Spatial indexes, so the above queries will use those indexes. Example:mysql> alter table postalcodes add spatial index zip_boundaries_spatial (geom);
Query OK, 35679 rows affected (5.30 sec)
Records: 35679 Duplicates: 0 Warnings: 0
mysql> explain select zip from postalcodes where st_contains(geom, point(-122.409153, 37.77765))\G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: postalcodes
type: range
possible_keys: zip_boundaries_spatial
key: zip_boundaries_spatial
key_len: 34
ref: NULL
rows: 1
Extra: Using where
1 row in set (0.01 sec)As we can see our spatial index is used for those functions. If we ignore or remove the index, the query will run significantly slower:mysql> select zip from postalcodes where st_within(point(-122.409153, 37.77765), geom);
+——-+
| zip |
+——-+
| 94103 |
+——-+
1 row in set (0.00 sec)
mysql> select zip from postalcodes ignore index (zip_boundaries_spatial) where st_contains(geom, point(-122.409153, 37.77765));
+——-+
| zip |
+——-+
| 94103 |
+——-+
1 row in set (4.24 sec)The InnoDB engine does not support spatial indexes, so those queries will be slow. As zip boundaries does not change often we can potentially use MyISAM tables for them.Find all coffee shops in a 10-mile radiusMySQL 5.6 supports st_distance functions with 2 drawbacks:It only supports planar coordinatesIt does not use indexGiven those major limitations, it is not very easy to use st_distance function for the geo enabled applications. If we simply need to find a distance between 2 points it is easier to store lat, lon directly and use harvesine expression (as described above).However it is still possible to use the st_distance() if we do not need exact numbers for the distance between 2 points (i.e. we only need to sort by distance). In our example, to find all coffee shops we will need to:Get the 10 mile radius MBR and use “within()” or “st_within()” functionUse st_distance function in the order by clauseFirst, we will calculate an envelope (square) to include approximately 10 miles, using the following approximations:1 degree of latitude ~= 69 miles1 degree of longitude ~= cos(latitude)*69 milesset @lat= 37.615223;
set @lon = -122.389979;
set @dist = 10;
set @rlon1 = @lon-@dist/abs(cos(radians(@lat))*69);
set @rlon2 = @lon+@dist/abs(cos(radians(@lat))*69);
set @rlat1 = @lat-(@dist/69);
set @rlat2 = @lat+(@dist/69);@lat and @lon in this example are the coordinates for the San Francisco International Airport (SFO).This will give us a set of coordinates (points) for the lower left and upper right corner of our square. Then we can use a MySQL’s envelope function to generate the MBR (we use linestring to draw a line between the 2 generated points and then envelope to draw an square):select astext(envelope(linestring(point(@rlon1, @rlat1), point(@rlon2, @rlat2))));The “envelope” will look like this:This is not exactly a 10-mile radius, however it may be close enough. Now we can find all points around SFO airport and sort by distance.mysql> select astext(shape), name from waypoints
where st_within(shape, envelope(linestring(point(@rlon1, @rlat1), point(@rlon2, @rlat2))))
order by st_distance(point(@lon, @lat), shape) limit 10;
+——————————–+——————————-+
| astext(shape) | name |
+——————————–+——————————-+
| POINT(-122.3890954 37.6145378) | Tram stop:Terminal A |
| POINT(-122.3899 37.6165902) | Tram stop:Terminal G |
| POINT(-122.3883973 37.6150806) | Fast Food Restaurant |
| POINT(-122.388929 37.6164584) | Restaurant:Ebisu |
| POINT(-122.3885347 37.6138365) | Fast Food Restaurant:Firewood |
| POINT(-122.38893 37.6132399) | Cafe:Amoura Café |
| POINT(-122.3894594 37.6129537) | Currency exchange |
| POINT(-122.39197849 37.614026) | Parking:Garage A |
| POINT(-122.3919031 37.6138567) | Tram stop:Garage A |
| POINT(-122.389176 37.612886) | Public telephone |
+——————————–+——————————-+
10 rows in set (0.02 sec)
mysql> explain select astext(shape), name from waypoints
where st_within(shape, envelope(linestring(point(@rlon1, @rlat1), point(@rlon2, @rlat2))))
order by st_distance(point(@lon, @lat), shape) limit 10\G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: waypoints
type: range
possible_keys: SHAPE
key: SHAPE
key_len: 34
ref: NULL
rows: 430
Extra: Using where; Using filesort
1 row in set (0.00 sec)As we can see from the explain it will use the spatial key on SHAPE and will only scan 430 rows, rather than millions of POIs.The query does not show the exact distance (this may be ok if we only need to output the points on the map).  If we need to show the distance we can use the harvesine formula to calculate that. For example we can create the following stored function to implement the calculations:create DEFINER = CURRENT_USER function harvesine (lat1 double, lon1 double, lat2 double, lon2 double) returns double
return 3956 * 2 * ASIN(SQRT(POWER(SIN((lat1 – abs(lat2)) * pi()/180 / 2), 2)
+ COS(abs(lat1) * pi()/180 ) * COS(abs(lat2) * pi()/180) * POWER(SIN((lon1 – lon2) * pi()/180 / 2), 2) )) ;And then use it for both order by and to displaying the distance. This query will also filter by “coffee”:mysql> select harvesine(y(shape), x(shape), @lat, @lon ) as dist, name from waypoints
where st_within(shape, envelope(linestring(point(@rlon1, @rlat1), point(@rlon2, @rlat2))))
and name like ‘%coffee%’ 
order by dist limit 10;
+——————-+———————————-+
| dist | name |
+——————-+———————————-+
| 3.462439728799387 | Cafe:Peet’s Coffee |
| 8.907725074619638 | Cafe:Nervous Dog Coffee |
| 9.169043718528133 | Cafe:Peet’s Coffee & Tea |
| 9.252659680688794 | Cafe:Martha and Bros Coffee |
| 9.492498547771854 | Cafe:Manor Coffee Shop |
| 9.559275248726559 | Cafe:Dynamo Donut & Coffee |
| 9.57775126039776 | Cafe:Starbucks Coffee |
| 9.585378425394556 | Cafe:Muddy’s Coffeehouse |
| 9.66247951599322 | Cafe:Martha and Bros. Coffee Co. |
| 9.671254753804767 | Cafe:Starbucks Coffee |
+——————-+———————————-+
10 rows in set (0.02 sec)ConclusionMySQL 5.6 implements an additional set of functions that can help create geo-enabled applications with MySQL. Storing polygons boundaries (ZIP code boundaries for example) is efficient and the new spatial functions (st_within, st_contains, etc) will produce correct results and will use spatial (rtree) indexes (for MyISAM tables only). The OpenGIS standard is very common and it is easy to obtain the data in this format or use the standard application which can “talk” this language.Unfortunately, st_distance function is not very usable for calculating distance between 2 points on Earth and it does not use an index. In this case it is still more feasible to calculate distances manually using the harvesine formula. Hopefully this will be fixed in the next mysql release.There are also some other limitations, for example st_union() function only supports 2 arguments and does not support an array, so it can’t be used in a queries like “select st_union(geom) from zipcodes group by state”.LinksNew spatial functions in MySQL 5.6Harvesine formula in WikipediaMy 2006 MySQL User Conference talk: geo search in MySQL and how to effectively calculate distance between 2 points in MySQL using harvesine formulaHenric Ingo compares the sptatial functions in MySQL. MariaDB, Postgress and MongoDB: talk at Percona Live conference, blog postOpensource POI database downloadGoogle maps API: I’ve used it to generate pictures for the examples in this postDistance between to points on Earth: online distance calculatorAnd finally, let me know in the comments how you use MySQL for geo enabled applications. In my next post I will talk more about basics of the MySQL geo spatial extension as well as Sphinx Search‘s implementation of the Geospatial functions.The post Using the new spatial functions in MySQL 5.6 for geo-enabled applications appeared first on MySQL Performance Blog.
via Planet MySQL
Using the new spatial functions in MySQL 5.6 for geo-enabled applications

If you’re studying math or science, you are probably pretty familiar with Wolfram Alpha as a tool for figuring out complicated equations. That makes it a pretty good tool for cheating, but not necessarily for learning. Today, the Wolfram Alpha team is launching a new service for learners, the Wolfram Problem Generator, that turns the "computational knowledge engine" on its head.
via TechCrunch
Wolfram Alpha Launches Problem Generator To Help Students Learn Math

Whether you’re learning to code or are already an experienced programmer, this GitHub repository is an incredible resource of free programming books.

Victor Felder updated this Stack Overflow list with new and corrected links and shared it over on GitHub for collaborative updating. You’ll find books on professional development, specific platforms like Android and Oracle Server, and about 80 programming languages. There are also lists in other languages.

Definitely worth a look for your continuing coding education. There’s nothing quite like free books!

Free Programming Books | GitHub via ITworld

Photo by Linda N..

via Lifehacker
Grab Over 500 Free Programming Books from GitHub

We’ve already talked a lot about how sitting all day is killing us, but what you might not know is just how good simply standing for a few hours a day can be. A new study found remarkable health benefits of standing versus sitting.

The BBC and the University of Chester conducted a simple experiment with a small group of ten volunteers. The volunteers were instructed to stand for at least three hours and wore throughout the day an accelerometer (to measure movement), as well as heart rate monitors and glucose monitors. The researchers took measurements on days when the volunteers stood and compared them to days when they sat.

The results:

• On standing days, the volunteers’ blood glucose levels went back to normal much more quickly after eating a meal compared to on the days when volunteers sat. High glucose levels have been linked with increased risks of heart disease and diabetes.
• Standing caused the volunteers to have a much higher heart rate (around 10 beats per minute higher), which adds up to burning about 50 calories more per hour versus sitting. Over a year, that adds up to about 30,000 more calories or 8 pounds of fat.

"If you want to put that into activity levels," Dr Buckley says, "then that would be the equivalent of running about 10 marathons a year. Just by standing up three or four hours in your day at work."

This was just a small, simple study, of course, but it’s just another indication that getting up out of your chair is good for you, particularly if you want to lose or maintain weight. (And, yes, of course, this isn’t an excuse not to regularly exercise.) Ready to get started? Check out our standing desk resources, and for even more fitness while working, consider a treadmill desk or do yoga at your standing desk.

Calorie burner: How much better is standing up than sitting? | BBC News

Photo by massdistraction.

via Lifehacker
Standing on Weekdays Burns Calories Like Running 10 Marathons a Year

Pen input is a great feature, but the complete package is better on paper than in person.

via Ars Technica
Review: Sony’s VAIO Flip 13 dies the death of a thousand cuts

If you prefer your cookies soft and round, rather than spread out into one giant layer, just bake the cookies in a muffin pan.

This is just one of a huge collection of food hacks over at MyFridgeFood, and the photo above kind of says it all. If you have a mini muffin pan, you can also easily make mini cookies.

If you prefer cookies with a crunch, you could also turn over a muffin pan and make cookie bowls instead.

MyFridgeFood – Just the Tips

via Lifehacker
Bake Soft, Perfectly Sized Cookies in a Muffin Pan

Dilbert readers – Please visit Dilbert.com to read this feature. Due to changes with our feeds, we are now making this RSS feed a link to Dilbert.com.
via Dilbert Daily Strip
Comic for October 12, 2013

Angry that Google is planning on using your face and name for the sake of advertisements? Here’s how to make them not.
via TechCrunch
How To Opt Out Of Google’s Weird New Ads That Use Your Face And Name