Search Results

Search found 3568 results on 143 pages for 'cost savings'.

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

Page 18/143 | < Previous Page | 14 15 16 17 18 19 20 21 22 23 24 25  | Next Page >

  • Database Insider - June 2014 issue now available

    - by Javier Puerta
    The June issue of the Database Insider newsletter is now available. (Full newsletter here) NEWS June 10: Oracle CEO Larry Ellison Live on the Future of Database Performance At a live webcast on June 10 at Oracle’s headquarters, Oracle CEO Larry Ellison is expected to announce the upcoming availability of Oracle Database In-Memory, which dramatically accelerates business decision-making by processing analytical queries in memory without requiring any changes to existing applications.Read More New Study Confirms Capital Expenditure Savings with Oracle Multitenant A new study finds that Oracle Multitenant, an option of Oracle Database 12c, drives significant savings in capital expenditures by enabling the consolidation of a large number of databases on the same number or fewer hardware resources.  Read More Read full newsletter here

    Read the article

  • Alternative to Amazon’s S3 service?

    - by Cory
    Just wondering if there is good alternative to Amazon's S3 service? I like S3 but the bandwidth cost is high. I looked at CouldFiles from Rackspace but the cost is even higher. I don't mind prepaying or having monthly payment in order to reduce the bandwidth cost greatly. Thank you for any help

    Read the article

  • Updating a Minimum spanning tree when a new edge is inserted

    - by Lynette
    Hello, I've been presented the following problem in University: Let G = (V, E) be an (undirected) graph with costs ce = 0 on the edges e € E. Assume you are given a minimum-cost spanning tree T in G. Now assume that a new edge is added to G, connecting two nodes v, tv € V with cost c. a) Give an efficient algorithm to test if T remains the minimum-cost spanning tree with the new edge added to G (but not to the tree T). Make your algorithm run in time O(|E|). Can you do it in O(|V|) time? Please note any assumptions you make about what data structure is used to represent the tree T and the graph G. b)Suppose T is no longer the minimum-cost spanning tree. Give a linear-time algorithm (time O(|E|)) to update the tree T to the new minimum-cost spanning tree. This is the solution I found: Let e1=(a,b) the new edge added Find in T the shortest path from a to b (BFS) if e1 is the most expensive edge in the cycle then T remains the MST else T is not the MST It seems to work but i can easily make this run in O(|V|) time, while the problem asks O(|E|) time. Am i missing something? By the way we are authorized to ask for help from anyone so I'm not cheating :D Thanks in advance

    Read the article

  • Neo4j Reading data / performing shortest path calculations on stored data

    - by paddydub
    I'm using the Batch_Insert example to insert Data into the database How can i read this data back from the database. I can't find any examples of how i do this. public static void CreateData() { // create the batch inserter BatchInserter inserter = new BatchInserterImpl( "var/graphdb", BatchInserterImpl.loadProperties( "var/neo4j.props" ) ); Map<String,Object> properties = new HashMap<String,Object>(); properties.put( "name", "Mr. Andersson" ); properties.put( "age", 29 ); long node1 = inserter.createNode( properties ); properties.put( "name", "Trinity" ); properties.remove( "age" ); long node2 = inserter.createNode( properties ); inserter.createRelationship( node1, node2, DynamicRelationshipType.withName( "KNOWS" ), null ); inserter.shutdown(); } I would like to store graph data in the database, graph.makeEdge( "s", "c", "cost", (double) 7 ); graph.makeEdge( "c", "e", "cost", (double) 7 ); graph.makeEdge( "s", "a", "cost", (double) 2 ); graph.makeEdge( "a", "b", "cost", (double) 7 ); graph.makeEdge( "b", "e", "cost", (double) 2 ); Dijkstra<Double> dijkstra = getDijkstra( graph, 0.0, "s", "e" ); What is the best method to store this kind data with 10000's of edges. Then run the Dijskra algorighm to find shortest path calculations using the stored graph data.

    Read the article

  • Approximate string matching with a letter confusion matrix?

    - by zigglenaut
    I'm trying to model a phonetic recognizer that has to isolate instances of words (strings of phones) out of a long stream of phones that doesn't have gaps between each word. The stream of phones may have been poorly recognized, with letter substitutions/insertions/deletions, so I will have to do approximate string matching. However, I want the matching to be phonetically-motivated, e.g. "m" and "n" are phonetically similar, so the substitution cost of "m" for "n" should be small, compared to say, "m" and "k". So, if I'm searching for [mein] "main", it would match the letter sequence [meim] "maim" with, say, cost 0.1, whereas it would match the letter sequence [meik] "make" with, say, cost 0.7. Similarly, there are differing costs for inserting or deleting each letter. I can supply a confusion matrix that, for each letter pair (x,y), gives the cost of substituting x with y, where x and y are any letter or the empty string. I know that there are tools available that do approximate matching such as agrep, but as far as I can tell, they do not take a confusion matrix as input. That is, the cost of any insertion/substitution/deletion = 1. My question is, are there any open-source tools already available that can do approximate matching with confusion matrices, and if not, what is a good algorithm that I can implement to accomplish this?

    Read the article

  • How to optimize my PostgreSQL DB for prefix search?

    - by asmaier
    I have a table called "nodes" with roughly 1.7 million rows in my PostgreSQL db =#\d nodes Table "public.nodes" Column | Type | Modifiers --------+------------------------+----------- id | integer | not null title | character varying(256) | score | double precision | Indexes: "nodes_pkey" PRIMARY KEY, btree (id) I want to use information from that table for autocompletion of a search field, showing the user a list of the ten titles having the highest score fitting to his input. So I used this query (here searching for all titles starting with "s") =# explain analyze select title,score from nodes where title ilike 's%' order by score desc; QUERY PLAN ----------------------------------------------------------------------------------------------------------------------- Sort (cost=64177.92..64581.38 rows=161385 width=25) (actual time=4930.334..5047.321 rows=161264 loops=1) Sort Key: score Sort Method: external merge Disk: 5712kB -> Seq Scan on nodes (cost=0.00..46630.50 rows=161385 width=25) (actual time=0.611..4464.413 rows=161264 loops=1) Filter: ((title)::text ~~* 's%'::text) Total runtime: 5260.791 ms (6 rows) This was much to slow for using it with autocomplete. With some information from Using PostgreSQL in Web 2.0 Applications I was able to improve that with a special index =# create index title_idx on nodes using btree(lower(title) text_pattern_ops); =# explain analyze select title,score from nodes where lower(title) like lower('s%') order by score desc limit 10; QUERY PLAN ------------------------------------------------------------------------------------------------------------------------------------------ Limit (cost=18122.41..18122.43 rows=10 width=25) (actual time=1324.703..1324.708 rows=10 loops=1) -> Sort (cost=18122.41..18144.60 rows=8876 width=25) (actual time=1324.700..1324.702 rows=10 loops=1) Sort Key: score Sort Method: top-N heapsort Memory: 17kB -> Bitmap Heap Scan on nodes (cost=243.53..17930.60 rows=8876 width=25) (actual time=96.124..1227.203 rows=161264 loops=1) Filter: (lower((title)::text) ~~ 's%'::text) -> Bitmap Index Scan on title_idx (cost=0.00..241.31 rows=8876 width=0) (actual time=90.059..90.059 rows=161264 loops=1) Index Cond: ((lower((title)::text) ~>=~ 's'::text) AND (lower((title)::text) ~<~ 't'::text)) Total runtime: 1325.085 ms (9 rows) So this gave me a speedup of factor 4. But can this be further improved? What if I want to use '%s%' instead of 's%'? Do I have any chance of getting a decent performance with PostgreSQL in that case, too? Or should I better try a different solution (Lucene?, Sphinx?) for implementing my autocomplete feature?

    Read the article

  • How can I work around SQL Server - Inline Table Value Function execution plan variation based on par

    - by Ovidiu Pacurar
    Here is the situation: I have a table value function with a datetime parameter ,lest's say tdf(p_date) , that filters about two million rows selecting those with column date smaller than p_date and computes some aggregate values on other columns. It works great but if p_date is a custom scalar value function (returning the end of day in my case) the execution plan is altered an the query goes from 1 sec to 1 minute execution time. A proof of concept table - 1K products, 2M rows: CREATE TABLE [dbo].[POC]( [Date] [datetime] NOT NULL, [idProduct] [int] NOT NULL, [Quantity] [int] NOT NULL ) ON [PRIMARY] The inline table value function: CREATE FUNCTION tdf (@p_date datetime) RETURNS TABLE AS RETURN ( SELECT idProduct, SUM(Quantity) AS TotalQuantity, max(Date) as LastDate FROM POC WHERE (Date < @p_date) GROUP BY idProduct ) The scalar value function: CREATE FUNCTION [dbo].[EndOfDay] (@date datetime) RETURNS datetime AS BEGIN DECLARE @res datetime SET @res=dateadd(second, -1, dateadd(day, 1, dateadd(ms, -datepart(ms, @date), dateadd(ss, -datepart(ss, @date), dateadd(mi,- datepart(mi,@date), dateadd(hh, -datepart(hh, @date), @date)))))) RETURN @res END Query 1 - Working great SELECT * FROM [dbo].[tdf] (getdate()) The end of execution plan: Stream Aggregate Cost 13% <--- Clustered Index Scan Cost 86% Query 2 - Not so great SELECT * FROM [dbo].[tdf] (dbo.EndOfDay(getdate())) The end of execution plan: Stream Aggregate Cost 4% <--- Filter Cost 12% <--- Clustered Index Scan Cost 86%

    Read the article

  • GridView's NewValues and OldValues empty in the OnRowUpdating event.

    - by Abe Miessler
    I have the GridView below. I am binding to a custom datasource in the code behind. It gets into the "OnRowUpdating" event just fine, but there are no NewValues or OldValues. Any suggestions as to how I can get these values? <asp:GridView ID="gv_Personnel" runat="server" OnRowDataBound="gv_Personnel_DataBind" OnRowCancelingEdit="gv_Personnel_CancelEdit" OnRowEditing="gv_Personnel_EditRow" OnRowUpdating="gv_Personnel_UpdateRow" AutoGenerateColumns="false" ShowFooter="true" DataKeyNames="BudgetLineID" AutoGenerateEditButton="true" AutoGenerateDeleteButton="true" > <Columns> <asp:BoundField HeaderText="Level of Staff" DataField="LineDescription" /> <%--<asp:BoundField HeaderText="Hrs/Units requested" DataField="NumberOfUnits" />--%> <asp:TemplateField HeaderText="Hrs/Units requested"> <ItemTemplate> <%# Eval("NumberOfUnits")%> </ItemTemplate> <EditItemTemplate> <asp:TextBox ID="tb_NumUnits" runat="server" Text='<%# Bind("NumberOfUnits")%>' /> </EditItemTemplate> </asp:TemplateField> <asp:BoundField HeaderText="Hrs/Units of Applicant Cost Share" DataField="" NullDisplayText="0" /> <asp:BoundField HeaderText="Hrs/Units of Partner Cost Share" DataField="" NullDisplayText="0" /> <asp:BoundField FooterStyle-Font-Bold="true" FooterText="TOTAL PERSONNEL SERVICES:" HeaderText="Rate" DataFormatString="{0:C}" DataField="UnitPrice" /> <asp:TemplateField HeaderText="Amount Requested" ItemStyle-HorizontalAlign="Right" FooterStyle-HorizontalAlign="Right" FooterStyle-BorderWidth="2" FooterStyle-Font-Bold="true"/> <asp:TemplateField HeaderText="Applicant Cost Share" ItemStyle-HorizontalAlign="Right" FooterStyle-HorizontalAlign="Right" FooterStyle-BorderWidth="2" FooterStyle-Font-Bold="true"/> <asp:TemplateField HeaderText="Partner Cost Share" ItemStyle-HorizontalAlign="Right" FooterStyle-HorizontalAlign="Right" FooterStyle-BorderWidth="2" FooterStyle-Font-Bold="true"/> <asp:TemplateField HeaderText="Total Projet Cost" ItemStyle-HorizontalAlign="Right" FooterStyle-HorizontalAlign="Right" FooterStyle-BorderWidth="2" FooterStyle-Font-Bold="true"/> </Columns> </asp:GridView>

    Read the article

  • Python code formatting

    - by Curious2learn
    In response to another question of mine, someone suggested that I avoid long lines in the code and to use PEP-8 rules when writing Python code. One of the PEP-8 rules suggested avoiding lines which are longer than 80 characters. I changed a lot of my code to comply with this requirement without any problems. However, changing the following line in the manner shown below breaks the code. Any ideas why? Does it have to do with the fact that what follows return command has to be in a single line? The line longer that 80 characters: def __str__(self): return "Car Type \n"+"mpg: %.1f \n" % self.mpg + "hp: %.2f \n" %(self.hp) + "pc: %i \n" %self.pc + "unit cost: $%.2f \n" %(self.cost) + "price: $%.2f "%(self.price) The line changed by using Enter key and Spaces as necessary: def __str__(self): return "Car Type \n"+"mpg: %.1f \n" % self.mpg + "hp: %.2f \n" %(self.hp) + "pc: %i \n" %self.pc + "unit cost: $%.2f \n" %(self.cost) + "price: $%.2f "%(self.price)

    Read the article

  • Dijkstras Algorithm exaplination java

    - by alchemey89
    Hi, I have found an implementation for dijkstras algorithm on the internet and was wondering if someone could help me understand how the code works. Many thanks private int nr_points=0; private int[][]Cost; private int []mask; private void dijkstraTSP() { if(nr_points==0)return; //algorithm=new String("Dijkstra"); nod1=new Vector(); nod2=new Vector(); weight=new Vector(); mask=new int[nr_points]; //initialise mask with zeros (mask[x]=1 means the vertex is marked as used) for(int i=0;i<nr_points;i++)mask[i]=0; //Dijkstra: int []dd=new int[nr_points]; int []pre=new int[nr_points]; int []path=new int[nr_points+1]; int init_vert=0,pos_in_path=0,new_vert=0; //initialise the vectors for(int i=0;i<nr_points;i++) { dd[i]=Cost[init_vert][i]; pre[i]=init_vert; path[i]=-1; } pre[init_vert]=0; path[0]=init_vert; pos_in_path++; mask[init_vert]=1; for(int k=0;k<nr_points-1;k++) { //find min. cost in dd for(int j=0;j<nr_points;j++) if(dd[j]!=0 && mask[j]==0){new_vert=j; break;} for(int j=0;j<nr_points;j++) if(dd[j]<dd[new_vert] && mask[j]==0 && dd[j]!=0)new_vert=j; mask[new_vert]=1; path[pos_in_path]=new_vert; pos_in_path++; for(int j=0;j<nr_points;j++) { if(mask[j]==0) { if(dd[j]>dd[new_vert]+Cost[new_vert][j]) { dd[j]=dd[new_vert]+Cost[new_vert][j]; } } } } //Close the cycle path[nr_points]=init_vert; //Save the solution in 3 vectors (for graphical purposes) for(int i=0;i<nr_points;i++) { nod1.addElement(path[i]); nod2.addElement(path[i+1]); weight.addElement(Cost[path[i]][path[i+1]]); } }

    Read the article

  • Maximum float value in php

    - by Alex Deem
    Is there a way to programmatically retrieve the maximum float value for php. Akin to FLT_MAX or std::numeric_limits< float >::max() in C / C++? I am using something like the following: $minimumCost = MAXIMUM_FLOAT_VALUE??; foreach ( $objects as $object ) { $cost = $object->CalculateCost(); if ( $cost < $minimumCost ) { $minimumCost = $cost; } } (using php 5.2)

    Read the article

  • Dijkstra's Algorithm explanation java

    - by alchemey89
    Hi, I have found an implementation for dijkstras algorithm on the internet and was wondering if someone could help me understand how the code works. Many thanks private int nr_points=0; private int[][]Cost; private int []mask; private void dijkstraTSP() { if(nr_points==0)return; //algorithm=new String("Dijkstra"); nod1=new Vector(); nod2=new Vector(); weight=new Vector(); mask=new int[nr_points]; //initialise mask with zeros (mask[x]=1 means the vertex is marked as used) for(int i=0;i<nr_points;i++)mask[i]=0; //Dijkstra: int []dd=new int[nr_points]; int []pre=new int[nr_points]; int []path=new int[nr_points+1]; int init_vert=0,pos_in_path=0,new_vert=0; //initialise the vectors for(int i=0;i<nr_points;i++) { dd[i]=Cost[init_vert][i]; pre[i]=init_vert; path[i]=-1; } pre[init_vert]=0; path[0]=init_vert; pos_in_path++; mask[init_vert]=1; for(int k=0;k<nr_points-1;k++) { //find min. cost in dd for(int j=0;j<nr_points;j++) if(dd[j]!=0 && mask[j]==0){new_vert=j; break;} for(int j=0;j<nr_points;j++) if(dd[j]<dd[new_vert] && mask[j]==0 && dd[j]!=0)new_vert=j; mask[new_vert]=1; path[pos_in_path]=new_vert; pos_in_path++; for(int j=0;j<nr_points;j++) { if(mask[j]==0) { if(dd[j]>dd[new_vert]+Cost[new_vert][j]) { dd[j]=dd[new_vert]+Cost[new_vert][j]; } } } } //Close the cycle path[nr_points]=init_vert; //Save the solution in 3 vectors (for graphical purposes) for(int i=0;i<nr_points;i++) { nod1.addElement(path[i]); nod2.addElement(path[i+1]); weight.addElement(Cost[path[i]][path[i+1]]); } }

    Read the article

  • Algorithm for generating an array of non-equal costs for a transport problem optimization

    - by Carlos
    I have an optimizer that solves a transportation problem, using a cost matrix of all the possible paths. The optimiser works fine, but if two of the costs are equal, the solution contains one more path that the minimum number of paths. (Think of it as load balancing routers; if two routes are same cost, you'll use them both.) I would like the minimum number of routes, and to do that I need a cost matrix that doesn't have two costs that are equal within a certain tolerance. At the moment, I'm passing the cost matrix through a baking function which tests every entry for equality to each of the other entries, and moves it a fixed percentage if it matches. However, this approach seems to require N^2 comparisons, and if the starting values are all the same, the last cost will be r^N bigger. (r is the arbitrary fixed percentage). Also there is the problem that by multiplying by the percentage, you end up on top of another value. So the problem seems to have an element of recursion, or at least repeated checking, which bloats the code. The current implementation is basically not very good (I won't paste my GOTO-using code here for you all to mock), and I'd like to improve it. Is there a name for what I'm after, and is there a standard implementation? Example: {1,1,2,3,4,5} (tol = 0.05) becomes {1,1.05,2,3,4,5}

    Read the article

  • How to generate a monotone MART ROC in R?

    - by user1521587
    I am using R and applying MART (Alg. for multiple additive regression trees) on a training set to build prediction models. When I look at the ROC curve, it is not monotone. I would be grateful if someone can help me with how I should fix this. I am guessing the issue is that initially, MART generates n trees and if these trees are not the same for all the models I am building, the results will not be comparable. Here are the steps I take: 1) Fix the false-negative cost, c_fn. Let cost = c(0, 1, c_fn, 0). 2) use the following line to build the mart model: mart(x, y, lx, martmode='class', niter=2000, cost.mtx=cost) where x is the matrix of training set variables, y is the observation matrix, lx is the matrix which specifies which of the variables in x is numerical, which one categorical. 3) I predict the test set observations using the mart model found in step 2 using this line: y_pred = martpred(x_test, probs=T) 4) I compute the false-positive and false-negative errors as follows: t = 1/(1+c_fn) %threshold based on Bayes optimal rule where c_fp=1 and c_fn. p_0 = length(which(y_test==1))/dim(y_test)[1] p_01 = sum(1*(y_pred[,2]t & y_test==0))/dim(y_test)[1] p_11 = sum(1*(y_pred[,2]t & y_test==1))/dim(y_test)[1] p_fp = p_01/(1-p_0) p_tp = p_11/p_0 5) repeat step 1-4 for a new false-negative cost.

    Read the article

  • How to optimize shopping carts for minimal prices?

    - by tangens
    I have a list of items I want to buy. The items are offered by different shops and different prices. The shops have individual delivery costs. I'm looking for an optimal shopping strategy (and a java library supporting it) to purchase all of the items with a minimal total price. Example: Item1 is offered at Shop1 for $100, at Shop2 for $111. Item2 is offered at Shop1 for $90, at Shop2 for $85. Delivery cost of Shop1: $10 if total order < $150; $0 otherwise Delivery cost of Shop2: $5 if total order < $50; $0 otherwise If I buy Item1 and Item2 at Shop1 the total cost is $100 + $90 +$0 = $190. If I buy Item1 and Item2 at Shop2 the total cost is $111 + $85 +$0 = $196. If I buy Item1 at Shop1 and Item2 at Shop2 the total cost is $100 + $10 + $85 + $0 = 195. I get the minimal price if I order Item1 at Shop1 and Item2 at Shop2: $195 Question I need some hints which algorithms may help me to solve optimization problems of this kind for number of items about 100 and number of shops about 20. I already looked at apache-math and its optimization package, but I have no idea what algorithm to look for.

    Read the article

  • how to show all added items into another activity, like: AddtoCart and ViewCart Functionality

    - by Stanley
    i am trying to make a shopping cart app, allowing user to choose category then select item to purchase, once user will click on any item to purchase, then showing that selected item into another activity with item image, name, cost, qty (to accept by user) and also providing add to cart functionality, now i want whenever user will click on Add to Cart button, then selected item need to show in ViewCart Activity, so here i am placing my AddtoCart Activity code, please tell me what i need to write to show added item(s) into ViewCart Category just like in shopping cart, In ViewCart activity i just want to show item title, cost and qty (entered by user):- public class AddtoCart extends Activity{ static final String KEY_TITLE = "title"; static final String KEY_COST = "cost"; static final String KEY_THUMB_URL = "imageUri"; @Override public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setContentView(R.layout.single); Intent in = getIntent(); String title = in.getStringExtra(KEY_TITLE); String thumb_url = in.getStringExtra(KEY_THUMB_URL); String cost = in.getStringExtra(KEY_COST); ImageLoader imageLoader = new ImageLoader(getApplicationContext()); ImageView imgv = (ImageView) findViewById(R.id.single_thumb); TextView txttitle = (TextView) findViewById(R.id.single_title); TextView txtcost = (TextView) findViewById(R.id.single_cost); txttitle.setText(title); txtcost.setText(cost); imageLoader.DisplayImage(thumb_url, imgv); // Save a reference to the quantity edit text final EditText editTextQuantity = (EditText) findViewById(R.id.edit_qty); ImageButton addToCartButton = (ImageButton) findViewById(R.id.img_add); addToCartButton.setOnClickListener(new OnClickListener() { public void onClick(View v) { // Check to see that a valid quantity was entered int quantity = 0; try { quantity = Integer.parseInt(editTextQuantity.getText() .toString()); if (quantity <= 0) { Toast.makeText(getBaseContext(), "Please enter a quantity of 1 or higher", Toast.LENGTH_SHORT).show(); return; } } catch (Exception e) { Toast.makeText(getBaseContext(), "Please enter a numeric quantity", Toast.LENGTH_SHORT).show(); return; } // Close the activity finish(); } }); }}

    Read the article

  • Simple aggregating query very slow in PostgreSql, any way to improve?

    - by Ash
    HI I have a table which holds files and their types such as CREATE TABLE files ( id SERIAL PRIMARY KEY, name VARCHAR(255), filetype VARCHAR(255), ... ); and another table for holding file properties such as CREATE TABLE properties ( id SERIAL PRIMARY KEY, file_id INTEGER CONSTRAINT fk_files REFERENCES files(id), size INTEGER, ... // other property fields ); The file_id field has an index. The file table has around 800k lines, and the properties table around 200k (not all files necessarily have/need a properties). I want to do aggregating queries, for example find the average size and standard deviation for all file types. But it's very slow - around 70 seconds for the latter query. I understand it needs a sequential scan, but still it seems too much. Here's the query SELECT f.filetype, avg(size), stddev(size) FROM files as f, properties as pr WHERE f.id = pr.file_id GROUP BY f.filetype; and the explain HashAggregate (cost=140292.20..140293.94 rows=116 width=13) (actual time=74013.621..74013.954 rows=110 loops=1) -> Hash Join (cost=6780.19..138945.47 rows=179564 width=13) (actual time=1520.104..73156.531 rows=179499 loops=1) Hash Cond: (f.id = pr.file_id) -> Seq Scan on files f (cost=0.00..108365.41 rows=1140941 width=9) (actual time=0.998..62569.628 rows=805270 loops=1) -> Hash (cost=3658.64..3658.64 rows=179564 width=12) (actual time=1131.053..1131.053 rows=179499 loops=1) -> Seq Scan on properties pr (cost=0.00..3658.64 rows=179564 width=12) (actual time=0.753..557.171 rows=179574 loops=1) Total runtime: 74014.520 ms Any ideas why it is so slow/how to make it faster?

    Read the article

  • Getting confused why i dont get expected amount ?

    - by Stackfan
    I have 1 result and which i will receive in Bank account, Based on that account i have to Put a balance to user account. How can you find the Handling cost from total tried 491.50 / 0.95 = 517.36 which is wrong ? It should be 500.00 (to my expectation) User balance requires 500.00 When 500.00 selected he gets 5% discount There is a handling cost for this ex: 1) Discount: 500.00 - 5% = 475.00 2) Handling cost: (475.00 x 0.034) + 0.35 = 16.50 3) Total: 475.00 + 16.50 = 491.50 So problem is from 491.50, i have to find atleast handling cost to get promised Balance. Any solution ? Cant figure it out myself...

    Read the article

  • Speeding up a group by date query on a big table in postgres

    - by zaius
    I've got a table with around 20 million rows. For arguments sake, lets say there are two columns in the table - an id and a timestamp. I'm trying to get a count of the number of items per day. Here's what I have at the moment. SELECT DATE(timestamp) AS day, COUNT(*) FROM actions WHERE DATE(timestamp) >= '20100101' AND DATE(timestamp) < '20110101' GROUP BY day; Without any indices, this takes about a 30s to run on my machine. Here's the explain analyze output: GroupAggregate (cost=675462.78..676813.42 rows=46532 width=8) (actual time=24467.404..32417.643 rows=346 loops=1) -> Sort (cost=675462.78..675680.34 rows=87021 width=8) (actual time=24466.730..29071.438 rows=17321121 loops=1) Sort Key: (date("timestamp")) Sort Method: external merge Disk: 372496kB -> Seq Scan on actions (cost=0.00..667133.11 rows=87021 width=8) (actual time=1.981..12368.186 rows=17321121 loops=1) Filter: ((date("timestamp") >= '2010-01-01'::date) AND (date("timestamp") < '2011-01-01'::date)) Total runtime: 32447.762 ms Since I'm seeing a sequential scan, I tried to index on the date aggregate CREATE INDEX ON actions (DATE(timestamp)); Which cuts the speed by about 50%. HashAggregate (cost=796710.64..796716.19 rows=370 width=8) (actual time=17038.503..17038.590 rows=346 loops=1) -> Seq Scan on actions (cost=0.00..710202.27 rows=17301674 width=8) (actual time=1.745..12080.877 rows=17321121 loops=1) Filter: ((date("timestamp") >= '2010-01-01'::date) AND (date("timestamp") < '2011-01-01'::date)) Total runtime: 17038.663 ms I'm new to this whole query-optimization business, and I have no idea what to do next. Any clues how I could get this query running faster?

    Read the article

  • multiple join query in entity framework

    - by gvLearner
    I have following tables tasks id | name | proj_id 1 | task1 | 1 2 | task2 | 1 3 | task3 | 1 projects id | name 1 | sample proj1 2 | demo project budget_versions id | version_name| proj_id 1 | 50 | 1 budgets id | cost | budget_version_id | task_id 1 | 3000 | 1 | 2 2 | 5000 | 1 | 1 I need to join these tables to get a result as below task_id | task_name | project_id | budget_version | budget_id | cost 1 | task1 | 1 | 1 | 2 |5000 2 | task2 | 1 | 1 | 1 |3000 3 | task3 | 1 | NULL | NULL |NULL select tsk.id,tsk.name, tsk.project_id, bgtver.id, bgt.id, bgt.cost from TASK tsk left outer join BUDGET_VERSIONS bgtver on tsk.project_id= bgtver.project_id left outer join BUDGETS bgt on bgtver.id = bgt.budget_version_id and tsk.id = bgt.task_id where bgtver.id = 1

    Read the article

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

< Previous Page | 14 15 16 17 18 19 20 21 22 23 24 25  | Next Page >