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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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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 MySql query to avoid using "Using filesort"

    - by usef_ksa
    I need your help to optimize the query to avoid using "Using filesort".The job of the query is to select all the articles that belongs to specific tag. The query is: "select title from tag,article where tag='Riyad' AND tag.article_id=article.id order by tag.article_id". the tables structure are the following: Tag table CREATE TABLE `tag` ( `tag` VARCHAR( 30 ) NOT NULL , `article_id` INT NOT NULL , INDEX ( `tag` ) ) ENGINE = MYISAM ; Article table CREATE TABLE `article` ( `id` INT NOT NULL AUTO_INCREMENT PRIMARY KEY , `title` VARCHAR( 60 ) NOT NULL ) ENGINE = MYISAM Sample data INSERT INTO `article` VALUES (1, 'About Riyad'); INSERT INTO `article` VALUES (2, 'About Newyork'); INSERT INTO `article` VALUES (3, 'About Paris'); INSERT INTO `article` VALUES (4, 'About London'); INSERT INTO `tag` VALUES ('Riyad', 1); INSERT INTO `tag` VALUES ('Saudia', 1); INSERT INTO `tag` VALUES ('Newyork', 2); INSERT INTO `tag` VALUES ('USA', 2); INSERT INTO `tag` VALUES ('Paris', 3); INSERT INTO `tag` VALUES ('France', 3);

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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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  • How can I make this Java code run faster?

    - 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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  • Optimizing ROW_NUMBER() in SQL Server

    - by BlueRaja
    We have a number of machines which record data into a database at sporadic intervals. For each record, I'd like to obtain the time period between this recording and the previous recording. I can do this using ROW_NUMBER as follows: WITH TempTable AS ( SELECT *, ROW_NUMBER() OVER (PARTITION BY Machine_ID ORDER BY Date_Time) AS Ordering FROM dbo.DataTable ) SELECT [Current].*, Previous.Date_Time AS PreviousDateTime FROM TempTable AS [Current] INNER JOIN TempTable AS Previous ON [Current].Machine_ID = Previous.Machine_ID AND Previous.Ordering = [Current].Ordering + 1 The problem is, it goes really slow (several minutes on a table with about 10k entries) - I tried creating separate indicies on Machine_ID and Date_Time, and a single joined-index, but nothing helps. Is there anyway to rewrite this query to go faster?

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  • Using * in SELECT Query

    - by libregeek
    I am currently porting an application written in MySQL3 and PHP4 to MySQL5 and PHP5. On analysis I found several SQL queries which uses "select * from tablename" even if only one column(field) is processed in PHP. The table has almost 60 columns and it has a primary key. In most cases, the only column used is id which is the primary key. Will there be any performance boost if I use queries in which the column names are explicitly mentioned instead of * ? (In this application there is only one method which we need all the columns and all other methods return only a subset of the columns)

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  • What is a data structure for quickly finding non-empty intersections of a list of sets?

    - by Andrey Fedorov
    I have a set of N items, which are sets of integers, let's assume it's ordered and call it I[1..N]. Given a candidate set, I need to find the subset of I which have non-empty intersections with the candidate. So, for example, if: I = [{1,2}, {2,3}, {4,5}] I'm looking to define valid_items(items, candidate), such that: valid_items(I, {1}) == {1} valid_items(I, {2}) == {1, 2} valid_items(I, {3,4}) == {2, 3} I'm trying to optimize for one given set I and a variable candidate sets. Currently I am doing this by caching items_containing[n] = {the sets which contain n}. In the above example, that would be: items_containing = [{}, {1}, {1,2}, {2}, {3}, {3}] That is, 0 is contained in no items, 1 is contained in item 1, 2 is contained in itmes 1 and 2, 2 is contained in item 2, 3 is contained in item 2, and 4 and 5 are contained in item 3. That way, I can define valid_items(I, candidate) = union(items_containing[n] for n in candidate). Is there any more efficient data structure (of a reasonable size) for caching the result of this union? The obvious example of space 2^N is not acceptable, but N or N*log(N) would be.

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  • Please help optimizing a long running query (left outer join, with 2 subqueries)

    - by 46and2
    Hi all. The query I need help with is: SELECT d.bn, d.4700, d.4500, ... , p.`Activity Description` FROM ( SELECT temp.bn, temp.4700, temp.4500, .... FROM `tdata` temp GROUP BY temp.bn HAVING (COUNT(temp.bn) = 1) ) d LEFT OUTER JOIN ( SELECT temp2.bn, max(temp2.FPE) AS max_fpe, temp2.`Activity Description` FROM `pdata` temp2 GROUP BY temp2.bn ) p ON p.bn = d.bn; The ... represents other fields that aren't really important to solving this problem. The issue is on the the second subquery - it is not using the index I have created and I am not sure why, it seems to be because of the way TEXT fields are handled. The first subquery uses the index I have created and runs quite snappy, however an explain on the second shows a 'Using temporary; Using filesort'. Please see the indexes I have created in the below table create statements. Can anyone help me optimize this? By way of quick explanation the first subquery is meant to only select records that have unique bn's, the second, while it looks a bit wacky (with the max function there which is not being used in the result set) is making sure that only one record from the right part of the join is included in the result set. My table create statements are CREATE TABLE `tdata` ( `BN` varchar(15) DEFAULT NULL, `4000` varchar(3) DEFAULT NULL, `5800` varchar(3) DEFAULT NULL, .... KEY `BN` (`BN`), KEY `idx_t3010`(`BN`,`4700`,`4500`,`4510`,`4520`,`4530`,`4570`,`4950`,`5000`,`5010`,`5020`,`5050`,`5060`,`5070`,`5100`) ) ENGINE=MyISAM DEFAULT CHARSET=utf8 CREATE TABLE `pdata` ( `BN` varchar(15) DEFAULT NULL, `FPE` datetime DEFAULT NULL, `Activity Description` text, .... KEY `BN` (`BN`), KEY `idx_programs_2009` (`BN`,`FPE`,`Activity Description`(100)) ) ENGINE=MyISAM DEFAULT CHARSET=utf8 Thanks!

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  • How to log slow queries in shared hosting MySQL?

    - by tomaszs
    I have a shared hosting where I have my website and MySQL database. I've installed a open source script for statistics (phpMyVisites) and it started to work very slow lately. It's written using some kind of framework and has many PHP files. I know that to find slow queries I can use slow query log functionality in MySQL. But on this shared hosting I can not use this method because I can not change my.cnf. I don't want to change my statistics script to other and I don't want to mess around with all files of this script to find out where to put diagnostics code to log queries manually. I would like to do it without changes in PHP code. So my question is: How to log slow queries in these coditions?: Can't change my.cnf to enable slow query log Can't change statistics script to other Don't know how scrpt is written and where mysql commands are issued Can't ask my provider for slow query log Is there any method to do this in simple, easy, fast way?

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