Search Results

Search found 26283 results on 1052 pages for 'temporary table'.

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 209/1052 | < Previous Page | 205 206 207 208 209 210 211 212 213 214 215 216  | Next Page >

  • mysql: Can I use two "where"s? Like, "SELECT * FROM table WHERE something and something"?

    - by KeriLynn
    I have a table with my products and I'm trying to write a page that would pull bracelets with certain colors from the database. So here's what I have right now (in php): $query = "SELECT * FROM products WHERE (products.colors LIKE '%black%')"; But I only want to select rows where the value for the column "category" equals "bracelet". I've tried a few different things, but I keep getting warnings and errors. I appreciate any help you can give, thank you!

    Read the article

  • How do I line up my textboxes without using a table? html/css

    - by SLC
    I want to display Name [Textbox] Age: [Textbox] BlahBlahCatfish: [Textbox] but if I simply plonk the code in, it gets lined up exactly as its lined up above. What I want is for it to be lined up like this: Name: [Textbox] Age: [Textbox] BlahBlahCatfish: [Textbox] Ordinarly I would use a Table but I am trying to get out of that habit and use lovely CSS. Ideas of how to do this without billions of divs and stuff?

    Read the article

  • Can emacs generate a table of comments and number sections of a document?

    - by mp3foley
    I'm writing a plain text document with numbered sections or chapters and am wondering if emacs can help with numbering and re-numbering sections. And of course would be great if it could then generate a table of contents as well. I have had a search on google and looked through the emacs wiki but did not come up with anything other than for latex stuff and possibly muse mode, but I would like to keep this as a plain text README style document. Thanks for any help or suggestions.

    Read the article

  • How should I structure my settings table with mysql?

    - by incrediman
    I want to use MySQL to store a bunch of admin settings - what's the best way to structure the table? Like this? Setting _|_ Value setting1 | a setting2 | b setting3 | c setting4 | d setting5 | e Or like this? |--------|_setting1_|_setting2_|_setting3_|_setting4_|_setting5_| Settings | a | b | c | d | e | Or maybe some other way?

    Read the article

  • SQL SERVER – Enable Identity Insert – Import Expert Wizard

    - by pinaldave
    I recently got email from old friend who told me that when he tries to execute SSIS package it fails with some identity error. After some debugging and opening his package we figure out that he has following issue. Let us see what kind of set up he had on his package. Source Table with Identity column Destination Table with Identity column Following checkbox was disabled in Import Expert Wizard (as per the image below) What did we do is we enabled the checkbox described as above and we fixed the problem he was having due to insertion in identity column. The reason he was facing this error because his destination table had IDENTITY property which will not allow any  insert from user. This value is automatically generated by system when new values are inserted in the table. However, when user manually tries to insert value in the table, it stops them and throws an error. As we enabled the checkbox “Enable Identity Insert”, this feature allowed the values to be insert in the identity field and this way from source database exact identity values were moved to destination table. Let me know if this blog post was easy to understand. Reference: Pinal Dave (http://blog.SQLAuthority.com), Filed under: Pinal Dave, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL, Technology

    Read the article

  • SQL SERVER – Importing CSV File Into Database – SQL in Sixty Seconds #018 – Video

    - by pinaldave
    Importing data into database is one of the most important tasks. I often receive questions regarding what is the quickest way to insert CSV data or how to import CSV Data into SQL Server Table. Honestly the process is very simple and the script is even simpler. In today’s SQL in Sixty Seconds Video we will learn how quickly we can insert CSV data into SQL Server. The steps to import CSV are very simple. Create Table Use Bulk Insert to import the data Verify the data Done! Absolutely it is that simple. More on Importing CSV Data: SQL SERVER – Import CSV File Into SQL Server Using Bulk Insert – Load Comma Delimited File Into SQL Server SQL SERVER – Import CSV File into Database Table Using SSIS SQL SERVER – Create a Comma Delimited List Using SELECT Clause From Table Column SQL SERVER – Comma Separated Values (CSV) from Table Column SQL SERVER – Comma Separated Values (CSV) from Table Column – Part 2 I encourage you to submit your ideas for SQL in Sixty Seconds. We will try to accommodate as many as we can. If we like your idea we promise to share with you educational material. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology, Video

    Read the article

  • Reading and conditionally updating N rows, where N > 100,000 for DNA Sequence processing

    - by makerofthings7
    I have a proof of concept application that uses Azure tables to associate DNA sequences to "something". Table 1 is the master table. It uniquely lists every DNA sequence. The PK is a load balanced hash of the RK. The RK is the unique encoded value of the DNA sequence. Additional tables are created per subject. Each subject has a list of N DNA sequences that have one reference in the Master table, where N is 100,000. It is possible for many tables to reference the same DNA sequence, but in this case only one entry will be present in the Master table. My Azure dilemma: I need to lock the reference in the Master table as I work with the data. I need to handle timeouts, and prevent other threads from overwriting my data as one C# thread is working with the information. Other threads need to realise that this is locked, and move onto other unlocked records and do the work. Ideally I'd like to get some progress report of how my computation is going, and have the option to cancel the process (and unwind the locks). Question What is the best approach for this? I'm looking at these code snippets for inspiration: http://blogs.msdn.com/b/jimoneil/archive/2010/10/05/azure-home-part-7-asynchronous-table-storage-pagination.aspx http://stackoverflow.com/q/4535740/328397

    Read the article

  • Smart defaults [SSDT]

    - by jamiet
    I’ve just discovered a new, somewhat hidden, feature in SSDT that I didn’t know about and figured it would be worth highlighting here because I’ll bet not many others know it either; the feature is called Smart Defaults. It gets around the problem of adding a NOT NULLable column to an existing table that has got data in it – previous to SSDT you would need to define a DEFAULT constraint however it does feel rather cumbersome to create an object purely for the purpose of pushing through a deployment – that’s the situation that Smart Defaults is meant to alleviate. The Smart Defaults option exists in the advanced section of a Publish Profile file: The description of the setting is “Automatically provides a default value when updating a table that contains data with a column that does not allow null values”, in other words checking that option will cause SSDT to insert an arbitrary default value into your newly created NON NULLable column. In case you’re wondering how it does it, here’s how: SSDT creates a DEFAULT CONSTRAINT at the same time as the column is created and then immediately removes that constraint: ALTER TABLE [dbo].[T1]    ADD [C1] INT NOT NULL,         CONSTRAINT [SD_T1_1df7a5f76cf44bb593506d05ff9a1e2b] DEFAULT 0 FOR [C1];ALTER TABLE [dbo].[T1] DROP CONSTRAINT [SD_T1_1df7a5f76cf44bb593506d05ff9a1e2b]; You can then update the value as appropriate in a Post-Deployment script. Pretty cool! On the downside, you can only specify this option for the whole project, not for an individual table or even an individual column – I’m not sure that I’d want to turn this on for an entire project as it could hide problems that a failed deployment would highlight, in other words smart defaults could be seen to be “papering over the cracks”. If you think that should be improved go and vote (and leave a comment) at [SSDT] Allow us to specify Smart defaults per table or even per column. @Jamiet

    Read the article

  • Smart defaults [SSDT]

    - by jamiet
    I’ve just discovered a new, somewhat hidden, feature in SSDT that I didn’t know about and figured it would be worth highlighting here because I’ll bet not many others know it either; the feature is called Smart Defaults. It gets around the problem of adding a NOT NULLable column to an existing table that has got data in it – previous to SSDT you would need to define a DEFAULT constraint however it does feel rather cumbersome to create an object purely for the purpose of pushing through a deployment – that’s the situation that Smart Defaults is meant to alleviate. The Smart Defaults option exists in the advanced section of a Publish Profile file: The description of the setting is “Automatically provides a default value when updating a table that contains data with a column that does not allow null values”, in other words checking that option will cause SSDT to insert an arbitrary default value into your newly created NON NULLable column. In case you’re wondering how it does it, here’s how: SSDT creates a DEFAULT CONSTRAINT at the same time as the column is created and then immediately removes that constraint: ALTER TABLE [dbo].[T1]    ADD [C1] INT NOT NULL,         CONSTRAINT [SD_T1_1df7a5f76cf44bb593506d05ff9a1e2b] DEFAULT 0 FOR [C1];ALTER TABLE [dbo].[T1] DROP CONSTRAINT [SD_T1_1df7a5f76cf44bb593506d05ff9a1e2b]; You can then update the value as appropriate in a Post-Deployment script. Pretty cool! On the downside, you can only specify this option for the whole project, not for an individual table or even an individual column – I’m not sure that I’d want to turn this on for an entire project as it could hide problems that a failed deployment would highlight, in other words smart defaults could be seen to be “papering over the cracks”. If you think that should be improved go and vote (and leave a comment) at [SSDT] Allow us to specify Smart defaults per table or even per column. @Jamiet

    Read the article

  • Solving Big Problems with Oracle R Enterprise, Part II

    - by dbayard
    Part II – Solving Big Problems with Oracle R Enterprise In the first post in this series (see https://blogs.oracle.com/R/entry/solving_big_problems_with_oracle), we showed how you can use R to perform historical rate of return calculations against investment data sourced from a spreadsheet.  We demonstrated the calculations against sample data for a small set of accounts.  While this worked fine, in the real-world the problem is much bigger because the amount of data is much bigger.  So much bigger that our approach in the previous post won’t scale to meet the real-world needs. From our previous post, here are the challenges we need to conquer: The actual data that needs to be used lives in a database, not in a spreadsheet The actual data is much, much bigger- too big to fit into the normal R memory space and too big to want to move across the network The overall process needs to run fast- much faster than a single processor The actual data needs to be kept secured- another reason to not want to move it from the database and across the network And the process of calculating the IRR needs to be integrated together with other database ETL activities, so that IRR’s can be calculated as part of the data warehouse refresh processes In this post, we will show how we moved from sample data environment to working with full-scale data.  This post is based on actual work we did for a financial services customer during a recent proof-of-concept. Getting started with the Database At this point, we have some sample data and our IRR function.  We were at a similar point in our customer proof-of-concept exercise- we had sample data but we did not have the full customer data yet.  So our database was empty.  But, this was easily rectified by leveraging the transparency features of Oracle R Enterprise (see https://blogs.oracle.com/R/entry/analyzing_big_data_using_the).  The following code shows how we took our sample data SimpleMWRRData and easily turned it into a new Oracle database table called IRR_DATA via ore.create().  The code also shows how we can access the database table IRR_DATA as if it was a normal R data.frame named IRR_DATA. If we go to sql*plus, we can also check out our new IRR_DATA table: At this point, we now have our sample data loaded in the database as a normal Oracle table called IRR_DATA.  So, we now proceeded to test our R function working with database data. As our first test, we retrieved the data from a single account from the IRR_DATA table, pull it into local R memory, then call our IRR function.  This worked.  No SQL coding required! Going from Crawling to Walking Now that we have shown using our R code with database-resident data for a single account, we wanted to experiment with doing this for multiple accounts.  In other words, we wanted to implement the split-apply-combine technique we discussed in our first post in this series.  Fortunately, Oracle R Enterprise provides a very scalable way to do this with a function called ore.groupApply().  You can read more about ore.groupApply() here: https://blogs.oracle.com/R/entry/analyzing_big_data_using_the1 Here is an example of how we ask ORE to take our IRR_DATA table in the database, split it by the ACCOUNT column, apply a function that calls our SimpleMWRR() calculation, and then combine the results. (If you are following along at home, be sure to have installed our myIRR package on your database server via  “R CMD INSTALL myIRR”). The interesting thing about ore.groupApply is that the calculation is not actually performed in my desktop R environment from which I am running.  What actually happens is that ore.groupApply uses the Oracle database to perform the work.  And the Oracle database is what actually splits the IRR_DATA table by ACCOUNT.  Then the Oracle database takes the data for each account and sends it to an embedded R engine running on the database server to apply our R function.  Then the Oracle database combines all the individual results from the calls to the R function. This is significant because now the embedded R engine only needs to deal with the data for a single account at a time.  Regardless of whether we have 20 accounts or 1 million accounts or more, the R engine that performs the calculation does not care.  Given that normal R has a finite amount of memory to hold data, the ore.groupApply approach overcomes the R memory scalability problem since we only need to fit the data from a single account in R memory (not all of the data for all of the accounts). Additionally, the IRR_DATA does not need to be sent from the database to my desktop R program.  Even though I am invoking ore.groupApply from my desktop R program, because the actual SimpleMWRR calculation is run by the embedded R engine on the database server, the IRR_DATA does not need to leave the database server- this is both a performance benefit because network transmission of large amounts of data take time and a security benefit because it is harder to protect private data once you start shipping around your intranet. Another benefit, which we will discuss in a few paragraphs, is the ability to leverage Oracle database parallelism to run these calculations for dozens of accounts at once. From Walking to Running ore.groupApply is rather nice, but it still has the drawback that I run this from a desktop R instance.  This is not ideal for integrating into typical operational processes like nightly data warehouse refreshes or monthly statement generation.  But, this is not an issue for ORE.  Oracle R Enterprise lets us run this from the database using regular SQL, which is easily integrated into standard operations.  That is extremely exciting and the way we actually did these calculations in the customer proof. As part of Oracle R Enterprise, it provides a SQL equivalent to ore.groupApply which it refers to as “rqGroupEval”.  To use rqGroupEval via SQL, there is a bit of simple setup needed.  Basically, the Oracle Database needs to know the structure of the input table and the grouping column, which we are able to define using the database’s pipeline table function mechanisms. Here is the setup script: At this point, our initial setup of rqGroupEval is done for the IRR_DATA table.  The next step is to define our R function to the database.  We do that via a call to ORE’s rqScriptCreate. Now we can test it.  The SQL you use to run rqGroupEval uses the Oracle database pipeline table function syntax.  The first argument to irr_dataGroupEval is a cursor defining our input.  You can add additional where clauses and subqueries to this cursor as appropriate.  The second argument is any additional inputs to the R function.  The third argument is the text of a dummy select statement.  The dummy select statement is used by the database to identify the columns and datatypes to expect the R function to return.  The fourth argument is the column of the input table to split/group by.  The final argument is the name of the R function as you defined it when you called rqScriptCreate(). The Real-World Results In our real customer proof-of-concept, we had more sophisticated calculation requirements than shown in this simplified blog example.  For instance, we had to perform the rate of return calculations for 5 separate time periods, so the R code was enhanced to do so.  In addition, some accounts needed a time-weighted rate of return to be calculated, so we extended our approach and added an R function to do that.  And finally, there were also a few more real-world data irregularities that we needed to account for, so we added logic to our R functions to deal with those exceptions.  For the full-scale customer test, we loaded the customer data onto a Half-Rack Exadata X2-2 Database Machine.  As our half-rack had 48 physical cores (and 96 threads if you consider hyperthreading), we wanted to take advantage of that CPU horsepower to speed up our calculations.  To do so with ORE, it is as simple as leveraging the Oracle Database Parallel Query features.  Let’s look at the SQL used in the customer proof: Notice that we use a parallel hint on the cursor that is the input to our rqGroupEval function.  That is all we need to do to enable Oracle to use parallel R engines. Here are a few screenshots of what this SQL looked like in the Real-Time SQL Monitor when we ran this during the proof of concept (hint: you might need to right-click on these images to be able to view the images full-screen to see the entire image): From the above, you can notice a few things (numbers 1 thru 5 below correspond with highlighted numbers on the images above.  You may need to right click on the above images and view the images full-screen to see the entire image): The SQL completed in 110 seconds (1.8minutes) We calculated rate of returns for 5 time periods for each of 911k accounts (the number of actual rows returned by the IRRSTAGEGROUPEVAL operation) We accessed 103m rows of detailed cash flow/market value data (the number of actual rows returned by the IRR_STAGE2 operation) We ran with 72 degrees of parallelism spread across 4 database servers Most of our 110seconds was spent in the “External Procedure call” event On average, we performed 8,200 executions of our R function per second (110s/911k accounts) On average, each execution was passed 110 rows of data (103m detail rows/911k accounts) On average, we did 41,000 single time period rate of return calculations per second (each of the 8,200 executions of our R function did rate of return calculations for 5 time periods) On average, we processed over 900,000 rows of database data in R per second (103m detail rows/110s) R + Oracle R Enterprise: Best of R + Best of Oracle Database This blog post series started by describing a real customer problem: how to perform a lot of calculations on a lot of data in a short period of time.  While standard R proved to be a very good fit for writing the necessary calculations, the challenge of working with a lot of data in a short period of time remained. This blog post series showed how Oracle R Enterprise enables R to be used in conjunction with the Oracle Database to overcome the data volume and performance issues (as well as simplifying the operations and security issues).  It also showed that we could calculate 5 time periods of rate of returns for almost a million individual accounts in less than 2 minutes. In a future post, we will take the same R function and show how Oracle R Connector for Hadoop can be used in the Hadoop world.  In that next post, instead of having our data in an Oracle database, our data will live in Hadoop and we will how to use the Oracle R Connector for Hadoop and other Oracle Big Data Connectors to move data between Hadoop, R, and the Oracle Database easily.

    Read the article

  • Bash script for mysql backup - error handling

    - by Jure1873
    I'm trying to backup a bunch of MyISAM tables in a way that would allow me to rsync/rdiff the backup directory to a remote location. I've came up with a script that dumps only the recently changed tables and sets the date of the file so that rsync can pick up only the changed ones, but now I don't know how to do the error handling - I would like the script to exit with a non 0 value if there are errors. How could I do that? #/bin/bash BKPDIR="/var/backups/db-mysql" mkdir -p $BKPDIR ERRORS=0 FIELDS="TABLE_SCHEMA, TABLE_NAME, UPDATE_TIME" W_COND="UPDATE_TIME >= DATE_ADD(CURDATE(), INTERVAL -2 DAY) AND TABLE_SCHEMA<>'information_schema'" mysql --skip-column-names -e "SELECT $FIELDS FROM information_schema.tables WHERE $W_COND;" | while read db table tstamp; do echo "DB: $db: TABLE: $table: ($tstamp)" mysqldump $db $table | gzip > $BKPDIR/$db-$table.sql.gz touch -d "$tstamp" $BKPDIR/$db-$table.sql.gz done exit $ERRORS

    Read the article

  • Help with dual booting Windows 8.1 Professional and Ubuntu 13.10

    - by user1292548
    I recently installed a clean version of Windows 8.1 Professional on my Lenovo Y500 (with Samsung 256GB 840 Pro SSD). I have Windows all set up and running normally. I am trying to dual boot Windows 8.1 and Ubuntu 13.10, but the installation procedure don't allow me to either "Install alongside..." or shows my SSD partitions correctly when I chose the "Something Else" option. I have created a 25GB partition of free space in the Windows disk manager, but on the installation screen on Ubuntu, it shows the whole drive as a free space. I have tried installing with a burned .ISO disk and a bootable USB, the results are the same for both. Windows Disk Management screen: http://imageshack.us/a/img855/9504/59zu.jpg The Ubuntu installation screen: http://imageshack.us/a/img62/2712/9g6i.jpg I've ran into this problem before when trying to dual boot Ubuntu and Windows 7 Professional a month ago. But I gave up and never resolved the issue. --EDIT-- I tried what Eero Aaltonen suggested, and this is my result: ubuntu@ubuntu:~$ sudo parted /dev/sda print Warning: /dev/sda contains GPT signatures, indicating that it has a GPT table. However, it does not have a valid fake msdos partition table, as it should. Perhaps it was corrupted -- possibly by a program that doesn't understand GPT partition tables. Or perhaps you deleted the GPT table, and are now using an msdos partition table. Is this a GPT partition table? Yes/No? yes Model: ATA Samsung SSD 840 (scsi) Disk /dev/sda: 256GB Sector size (logical/physical): 512B/512B Partition Table: gpt Number Start End Size File system Name Flags ubuntu@ubuntu:~$

    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 | 205 206 207 208 209 210 211 212 213 214 215 216  | Next Page >