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  • Web Search Engine Optimization - 3 Important Off-Page Strategies

    Trying to improve your Web search engine optimization plan? Did you know that what you are doing off your website to improve search engine optimization (SEO) is just as important as what you do directly on your website? The major search engines are just as concerned with your "off-page" tactics and behavior; and what you are doing everywhere else on the Web will definitely figure into their algorithms for search result rankings.

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  • Can Search Engine Optimization Actually Help Your Online Business

    Search engine optimization or SEO is a concept that has come about in the internet world and it sure enough is a concept that is guaranteed to save a dying website in no time. If you have heard quite a bit about search engine optimization and how best it can save your business from going down the drain but do not know how can utilize the service to save your online business, then you have come to the right place because, here, you are going to find out about some very important information that will help you understand this particular concept better.

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  • Search Engine Optimization - Developing Your Powerful SEO Gameplan

    Deciding on what to do with your traffic generation business may be a little bit sticky. Should you change your search engine optimization gameplan? Or stick with what you have right now? Given the fact that half million of search engine optimization experts are doing the same thing like you. Developing an SEO didactic tactic plays a big part in your SEO gameplan.

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  • Easy Search Engine Optimization Strategies

    Search Engine Optimization or SEO is a technical sounding term that's simply a strategy for making your website relevant to your target audience and structuring your website in such a way that it will be found by search engines when your keywords are entered by users. Here a few easy strategies for incorporating SEO into your website: Identify your Keywords Before you do any optimization work on your website you first have to know what keywords are being used by your target market. For example if you are selling home repair guides, you'll need to know the...

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  • The Evolution of Internet Marketing and Search Engine Optimization

    Search Engine Optimization (SEO) is a process of increasing the quality and volume of traffic to a website via a search engine result which is purely organic and not paid. The higher the website appears on a search result, the greater the chance of traffic going to the website. Therefore not only does it create a web presence for a website but has spawned a global industry of advertising and search engine optimization.

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  • What Internet Marketers Need to Avoid in Search Engine Optimization

    Many internet marketers are self-starters and test market products on a shoestring. Doing so means taking search engine optimization or SEO into one's own hands. Knowing the basics of search engine optimization are critical to achieving a high ranking in search engines for specific keywords. However, there are a number of common pitfalls to avoid.

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  • SEO - Search Engine Optimization Working For You

    SEO (search engine optimization), sometimes referred to as natural or organic search optimization, website SEO, or just plain old SEO, is the process of ensuring that the ranking of your website with search engines i.e. Google, Yahoo etc puts your web site near the top of searches. Natural or Organic search results are "free" i.e., you do not pay for a listing in the search results pages for your keywords. This means you need to do all the work.

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  • How Search Engine Optimization Can Improve Your Business

    Before I move on to how Search Engine Optimization in Toronto can improve your business, you need to familiarize yourself with search engine optimization (SEO). Many people think SEO is a very complex process with many steps and procedures involved. It is true to a certain extent as there are many things which have to be done in SEO, but SEO is simplified if you know the basics well.

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  • Content Optimization For Your Web Page

    An important step when developing web pages is content optimization. Search Engine Optimization (SEO) is big business in the world of online navigation. Therefore, loading your web page with relevant keywords so a search engine will rank you in the top ten is essential.

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  • SEO Optimization - An Effective Tool For Business

    SEO optimization also known as Search Engine Optimization is an important part of internet marketing operation. And, if you are thinking of improving and endorsing your website than this is the best options which you can select. It has also become an effective tool for every company that is used for promoting their website.

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  • Search Engine Optimization - Developing Your Powerful SEO Gameplan

    Deciding on what to do with your traffic generation business may be a little bit sticky. Should you change your search engine optimization gameplan? Or stick with what you have right now? Given the fact that half million of search engine optimization experts are doing the same thing like you. Developing an SEO didactic tactic plays a big part in your SEO gameplan.

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  • The Basics of Search Engine Optimization

    What is search engine optimization? Search engine optimization or 'SEO' for short is method of using keywords or phrases of keywords that are targeted for your site helping it to rank high in the search engine results. What this means is that when someone types a keyword or phrase that you have chosen to target your site should come out on top if done right.

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  • Java: micro-optimizing array manipulation

    - by Martin Wiboe
    Hello all, I am trying to make a Java port of a simple feed-forward neural network. This obviously involves lots of numeric calculations, so I am trying to optimize my central loop as much as possible. The results should be correct within the limits of the float data type. My current code looks as follows (error handling & initialization removed): /** * Simple implementation of a feedforward neural network. The network supports * including a bias neuron with a constant output of 1.0 and weighted synapses * to hidden and output layers. * * @author Martin Wiboe */ public class FeedForwardNetwork { private final int outputNeurons; // No of neurons in output layer private final int inputNeurons; // No of neurons in input layer private int largestLayerNeurons; // No of neurons in largest layer private final int numberLayers; // No of layers private final int[] neuronCounts; // Neuron count in each layer, 0 is input // layer. private final float[][][] fWeights; // Weights between neurons. // fWeight[fromLayer][fromNeuron][toNeuron] // is the weight from fromNeuron in // fromLayer to toNeuron in layer // fromLayer+1. private float[][] neuronOutput; // Temporary storage of output from previous layer public float[] compute(float[] input) { // Copy input values to input layer output for (int i = 0; i < inputNeurons; i++) { neuronOutput[0][i] = input[i]; } // Loop through layers for (int layer = 1; layer < numberLayers; layer++) { // Loop over neurons in the layer and determine weighted input sum for (int neuron = 0; neuron < neuronCounts[layer]; neuron++) { // Bias neuron is the last neuron in the previous layer int biasNeuron = neuronCounts[layer - 1]; // Get weighted input from bias neuron - output is always 1.0 float activation = 1.0F * fWeights[layer - 1][biasNeuron][neuron]; // Get weighted inputs from rest of neurons in previous layer for (int inputNeuron = 0; inputNeuron < biasNeuron; inputNeuron++) { activation += neuronOutput[layer-1][inputNeuron] * fWeights[layer - 1][inputNeuron][neuron]; } // Store neuron output for next round of computation neuronOutput[layer][neuron] = sigmoid(activation); } } // Return output from network = output from last layer float[] result = new float[outputNeurons]; for (int i = 0; i < outputNeurons; i++) result[i] = neuronOutput[numberLayers - 1][i]; return result; } private final static float sigmoid(final float input) { return (float) (1.0F / (1.0F + Math.exp(-1.0F * input))); } } I am running the JVM with the -server option, and as of now my code is between 25% and 50% slower than similar C code. What can I do to improve this situation? Thank you, Martin Wiboe

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  • Optimize css vs Google page speed is messing with me

    - by The Disintegrator
    I'm using google page speed and it's telling me my css is inefficient... Very inefficient rules (good to fix on any page): * table.fancy thead td Tag key with 2 descendant selectors and Class overly qualified with tag * table.fancy tfoot td Tag key with 2 descendant selectors and Class overly qualified with tag The css rules are table.fancy {border: 1px solid white; padding:5px} table.fancy td {background:#656165} table.fancy thead td, table.fancy tfoot td {background:#767276} I want the header and footer in a different background color than the body of the table (a data table) On what grounds this is inefficient? How to make it more efficient? I will not add a class to the thead and tfoot for googles's sake.

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  • MySql multiple selects batching in .net

    - by Amith George
    I have a situation in my application. For each x-axis point in my chart, I am plotting 5 y-axis values. To calculate each of these 5 values, I need to make 4 different queries. Ie, for each x-axis point I need to fire 20 sql queries. Now, I need to plot 40 such points in the my chart. Its resulting in a pathetic performance where it takes close to a minute to get all the data back from the database. Each of 4 different queries consists of a join between 2 tables. One has only 6 rows. The other close to 10,000. Each of the 4 queries has different WHERE clauses, so they are different queries. For each point in the x-axis, only the values for the where clauses change. I have tried combining each of the 4 queries into one big string. Basically batch the four selects. These are again batched for each y-axis value. So, for each x-axis point, I am now firing one big command that consists of 20 different select statements. Technically, I should be experiencing a big performance boost, right? Instead of hitting the db 40x5x4 = 800 times, I am now hitting it just 40 times. But instead of taking 60 seconds, it taking 50-55 seconds... not much of a help. I am using MySql 5.1, and the 6.1 version of its .Net connector. What can I do to improve the performance? Edit: One of the 4 queries is as follows: SELECT SUM(TIME_TO_SEC(TIMEDIFF(T1.col2, T1.col1))* T2.col1 / (3600 *1000)) AS TotalTime FROM Table T1 JOIN Table T2 ON T1.col3 = T2.col3 WHERE T1.col4 = 'i' AND T1.col1 >= '2009-12-25 00:00:00' AND T1.col2 <= '2009-12-26 00:00:00'; The other 3 queries are similar, only the where clause changes slightly. This set of 4 queries is fired 5 times. The first 3 times against the join of table T1 and T2, passing in different values for col4. And the next two times against the join of table T3 and T2 passing in different values for col4. These 5 values are the y-axis values for a particular x-axis point. The data returned by all these queries is the same format. so, we tried doing a UNION ALL on all these queries. No substantial difference. One strange thing, however, after indexing the foreign key on the table T1 [while it contained over a lakh records], the queries were using the index, but they had become slower. At times, the queries would take double the time to return the data.

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  • optimizing an sql query using inner join and order by

    - by Sergio B
    I'm trying to optimize the following query without success. Any idea where it could be indexed to prevent the temporary table and the filesort? EXPLAIN SELECT SQL_NO_CACHE `groups`.* FROM `groups` INNER JOIN `memberships` ON `groups`.id = `memberships`.group_id WHERE ((`memberships`.user_id = 1) AND (`memberships`.`status_code` = 1 AND `memberships`.`manager` = 0)) ORDER BY groups.created_at DESC LIMIT 5;` +----+-------------+-------------+--------+--------------------------+---------+---------+---------------------------------------------+------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------------+--------+--------------------------+---------+---------+---------------------------------------------+------+----------------------------------------------+ | 1 | SIMPLE | memberships | ref | grp_usr,grp,usr,grp_mngr | usr | 5 | const | 5 | Using where; Using temporary; Using filesort | | 1 | SIMPLE | groups | eq_ref | PRIMARY | PRIMARY | 4 | sportspool_development.memberships.group_id | 1 | | +----+-------------+-------------+--------+--------------------------+---------+---------+---------------------------------------------+------+----------------------------------------------+ 2 rows in set (0.00 sec) +--------+------------+-----------------------------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+ | Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | +--------+------------+-----------------------------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+ | groups | 0 | PRIMARY | 1 | id | A | 6 | NULL | NULL | | BTREE | | | groups | 1 | index_groups_on_name | 1 | name | A | 6 | NULL | NULL | YES | BTREE | | | groups | 1 | index_groups_on_privacy_setting | 1 | privacy_setting | A | 6 | NULL | NULL | YES | BTREE | | | groups | 1 | index_groups_on_created_at | 1 | created_at | A | 6 | NULL | NULL | YES | BTREE | | | groups | 1 | index_groups_on_id_and_created_at | 1 | id | A | 6 | NULL | NULL | | BTREE | | | groups | 1 | index_groups_on_id_and_created_at | 2 | created_at | A | 6 | NULL | NULL | YES | BTREE | | +--------+------------+-----------------------------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+ +-------------+------------+----------------------------------------------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+ | Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | +-------------+------------+----------------------------------------------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+ | memberships | 0 | PRIMARY | 1 | id | A | 2 | NULL | NULL | | BTREE | | | memberships | 0 | grp_usr | 1 | group_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 0 | grp_usr | 2 | user_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | grp | 1 | group_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | usr | 1 | user_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | grp_mngr | 1 | group_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | grp_mngr | 2 | manager | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | complex_index | 1 | group_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | complex_index | 2 | user_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | complex_index | 3 | status_code | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | complex_index | 4 | manager | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | index_memberships_on_user_id_and_status_code_and_manager | 1 | user_id | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | index_memberships_on_user_id_and_status_code_and_manager | 2 | status_code | A | 2 | NULL | NULL | YES | BTREE | | | memberships | 1 | index_memberships_on_user_id_and_status_code_and_manager | 3 | manager | A | 2 | NULL | NULL | YES | BTREE | | +-------------+------------+----------------------------------------------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+

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  • Should i really use integer primary IDs?

    - by arthurprs
    For example, i always generate an auto-increment field for the users table, but i also specifies an UNIQUE index on their usernames. There is situations that i first need to get the userId for a given username and then execute the desired query. Or use a JOIN in the desired query. It's 2 trips to the database or a JOIN vs. a varchar index The above is just an example There is a real performance benefit on INT over small VARCHAR indexes? Thanks in advance!

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  • Is possible to reuse subqueries?

    - by Gothmog
    Hello, I'm having some problems trying to perform a query. I have two tables, one with elements information, and another one with records related with the elements of the first table. The idea is to get in the same row the element information plus several records information. Structure could be explain like this: table [ id, name ] [1, '1'], [2, '2'] table2 [ id, type, value ] [1, 1, '2009-12-02'] [1, 2, '2010-01-03'] [1, 4, '2010-01-03'] [2, 1, '2010-01-02'] [2, 2, '2010-01-02'] [2, 2, '2010-01-03'] [2, 3, '2010-01-07'] [2, 4, '2010-01-07'] And this is want I would like to achieve: result [id, name, Column1, Column2, Column3, Column4] [1, '1', '2009-12-02', '2010-01-03', , '2010-01-03'] [2, '2', '2010-01-02', '2010-01-02', '2010-01-07', '2010-01-07'] The following query gets the proper result, but it seems to me extremely inefficient, having to iterate table2 for each column. Would be possible in anyway to do a subquery and reuse it? SELECT a.id, a.name, (select min(value) from table2 t where t.id = subquery.id and t.type = 1 group by t.type) as Column1, (select min(value) from table2 t where t.id = subquery.id and t.type = 2 group by t.type) as Column2, (select min(value) from table2 t where t.id = subquery.id and t.type = 3 group by t.type) as Column3, (select min(value) from table2 t where t.id = subquery.id and t.type = 4 group by t.type) as Column4 FROM (SELECT distinct id FROM table2 t WHERE (t.type in (1, 2, 3, 4)) AND t.value between '2010-01-01' and '2010-01-07') as subquery LEFT JOIN table a ON a.id = subquery.id

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  • Write a compiler for a language that looks ahead and multiple files?

    - by acidzombie24
    In my language I can use a class variable in my method when the definition appears below the method. It can also call methods below my method and etc. There are no 'headers'. Take this C# example. class A { public void callMethods() { print(); B b; b.notYetSeen(); public void print() { Console.Write("v = {0}", v); } int v=9; } class B { public void notYetSeen() { Console.Write("notYetSeen()\n"); } } How should I compile that? what i was thinking is: pass1: convert everything to an AST pass2: go through all classes and build a list of define classes/variable/etc pass3: go through code and check if there's any errors such as undefined variable, wrong use etc and create my output But it seems like for this to work I have to do pass 1 and 2 for ALL files before doing pass3. Also it feels like a lot of work to do until I find a syntax error (other than the obvious that can be done at parse time such as forgetting to close a brace or writing 0xLETTERS instead of a hex value). My gut says there is some other way. Note: I am using bison/flex to generate my compiler.

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  • PostgreSQL - Why are some queries on large datasets so incredibly slow

    - by Brad Mathews
    Hello, I have two types of queries I run often on two large datasets. They run much slower than I would expect them to. The first type is a sequential scan updating all records: Update rcra_sites Set street = regexp_replace(street,'/','','i') rcra_sites has 700,000 records. It takes 22 minutes from pgAdmin! I wrote a vb.net function that loops through each record and sends an update query for each record (yes, 700,000 update queries!) and it runs in less than half the time. Hmmm.... The second type is a simple update with a relation and then a sequential scan: Update rcra_sites as sites Set violations='No' From narcra_monitoring as v Where sites.agencyid=v.agencyid and v.found_violation_flag='N' narcra_monitoring has 1,700,000 records. This takes 8 minutes. The query planner refuses to use my indexes. The query runs much faster if I start with a set enable_seqscan = false;. I would prefer if the query planner would do its job. I have appropriate indexes, I have vacuumed and analyzed. I optimized my shared_buffers and effective_cache_size best I know to use more memory since I have 4GB. My hardware is pretty darn good. I am running v8.4 on Windows 7. Is PostgreSQL just this slow? Or am I still missing something? Thanks! Brad

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  • Optimizing mathematics on arrays of floats in Ada 95 with GNATC

    - by mat_geek
    Consider the bellow code. This code is supposed to be processing data at a fixed rate, in one second batches, It is part of an overal system and can't take up too much time. When running over 100 lots of 1 seconds worth of data the program takes 35 seconds; or 35%. How do I improce the code to get the processing time down to a minimum? The code will be running on an Intel Pentium-M which is a P3 with SSE2. package FF is new Ada.Numerics.Generic_Elementary_Functions(Float); N : constant Integer := 820; type A is array(1 .. N) of Float; type A3 is array(1 .. 3) of A; procedure F(state : in out A3; result : out A3; l : in A; r : in A) is s : Float; t : Float; begin for i in 1 .. N loop t := l(i) + r(i); t := t / 2.0; state(1)(i) := t; state(2)(i) := t * 0.25 + state(2)(i) * 0.75; state(3)(i) := t * 1.0 /64.0 + state(2)(i) * 63.0 /64.0; for r in 1 .. 3 loop s := state(r)(i); t := FF."**"(s, 6.0) + 14.0; if t > MAX then t := MAX; elsif t < MIN then t := MIN; end if; result(r)(i) := FF.Log(t, 2.0); end loop; end loop; end;

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  • Postgres query optmization

    - by hdx
    Hey guys, trying to optimize this query to solve a duplicate user issue: SELECT userid, 'ismaster' AS name, 'false' AS propvalue FROM user WHERE userid NOT IN (SELECT userid FROM userprop WHERE name = 'ismaster'); The problem is that the select after the NOT IN is 120.000 records and it's taking forever. Any suggestion?

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  • Optimizing mathematics on arrays of floats in Ada 95 with GNAT

    - by mat_geek
    Consider the bellow code. This code is supposed to be processing data at a fixed rate, in one second batches, It is part of an overal system and can't take up too much time. When running over 100 lots of 1 seconds worth of data the program takes 35 seconds (or 35%), executing this function in a loop. The test loop is timed specifically with Ada.RealTime. The data is pregenerated so the majority of the execution time is definatetly in this loop. How do I improce the code to get the processing time down to a minimum? The code will be running on an Intel Pentium-M which is a P3 with SSE2. package FF is new Ada.Numerics.Generic_Elementary_Functions(Float); N : constant Integer := 820; type A is array(1 .. N) of Float; type A3 is array(1 .. 3) of A; procedure F(state : in out A3; result : out A3; l : in A; r : in A) is s : Float; t : Float; begin for i in 1 .. N loop t := l(i) + r(i); t := t / 2.0; state(1)(i) := t; state(2)(i) := t * 0.25 + state(2)(i) * 0.75; state(3)(i) := t * 1.0 /64.0 + state(2)(i) * 63.0 /64.0; for r in 1 .. 3 loop s := state(r)(i); t := FF."**"(s, 6.0) + 14.0; if t > MAX then t := MAX; elsif t < MIN then t := MIN; end if; result(r)(i) := FF.Log(t, 2.0); end loop; end loop; end; psuedocode for testing create two arrays of 80 random A3 arrays, called ls and rs; init the state and result A3 array record the realtime time now, called last for i in 1 .. 100 loop for j in 1 .. 80 loop F(state, result, ls(j), rs(j)); end loop; end loop; record the realtime time now, called curr output the duration between curr and last

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