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  • ODI 11g – Oracle Multi Table Insert

    - by David Allan
    With the IKM Oracle Multi Table Insert you can generate Oracle specific DML for inserting into multiple target tables from a single query result – without reprocessing the query or staging its result. When designing this to exploit the IKM you must split the problem into the reusable parts – the select part goes in one interface (I named SELECT_PART), then each target goes in a separate interface (INSERT_SPECIAL and INSERT_REGULAR). So for my statement below… /*INSERT_SPECIAL interface */ insert  all when 1=1 And (INCOME_LEVEL > 250000) then into SCOTT.CUSTOMERS_NEW (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) values (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) /* INSERT_REGULAR interface */ when 1=1  then into SCOTT.CUSTOMERS_SPECIAL (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) values (ID, NAME, GENDER, BIRTH_DATE, MARITAL_STATUS, INCOME_LEVEL, CREDIT_LIMIT, EMAIL, USER_CREATED, DATE_CREATED, USER_MODIFIED, DATE_MODIFIED) /*SELECT*PART interface */ select        CUSTOMERS.EMAIL EMAIL,     CUSTOMERS.CREDIT_LIMIT CREDIT_LIMIT,     UPPER(CUSTOMERS.NAME) NAME,     CUSTOMERS.USER_MODIFIED USER_MODIFIED,     CUSTOMERS.DATE_MODIFIED DATE_MODIFIED,     CUSTOMERS.BIRTH_DATE BIRTH_DATE,     CUSTOMERS.MARITAL_STATUS MARITAL_STATUS,     CUSTOMERS.ID ID,     CUSTOMERS.USER_CREATED USER_CREATED,     CUSTOMERS.GENDER GENDER,     CUSTOMERS.DATE_CREATED DATE_CREATED,     CUSTOMERS.INCOME_LEVEL INCOME_LEVEL from    SCOTT.CUSTOMERS   CUSTOMERS where    (1=1) Firstly I create a SELECT_PART temporary interface for the query to be reused and in the IKM assignment I state that it is defining the query, it is not a target and it should not be executed. Then in my INSERT_SPECIAL interface loading a target with a filter, I set define query to false, then set true for the target table and execute to false. This interface uses the SELECT_PART query definition interface as a source. Finally in my final interface loading another target I set define query to false again, set target table to true and execute to true – this is the go run it indicator! To coordinate the statement construction you will need to create a package with the select and insert statements. With 11g you can now execute the package in simulation mode and preview the generated code including the SQL statements. Hopefully this helps shed some light on how you can leverage the Oracle MTI statement. A similar IKM exists for Teradata. The ODI IKM Teradata Multi Statement supports this multi statement request in 11g, here is an extract from the paper at www.teradata.com/white-papers/born-to-be-parallel-eb3053/ Teradata Database offers an SQL extension called a Multi-Statement Request that allows several distinct SQL statements to be bundled together and sent to the optimizer as if they were one. Teradata Database will attempt to execute these SQL statements in parallel. When this feature is used, any sub-expressions that the different SQL statements have in common will be executed once, and the results shared among them. It works in the same way as the ODI MTI IKM, multiple interfaces orchestrated in a package, each interface contributes some SQL, the last interface in the chain executes the multi statement.

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  • The blocking nature of aggregates

    - by Rob Farley
    I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here.  In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

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  • The blocking nature of aggregates

    - by Rob Farley
    I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here.  In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

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  • Getting started with Oracle Database In-Memory Part III - Querying The IM Column Store

    - by Maria Colgan
    In my previous blog posts, I described how to install, enable, and populate the In-Memory column store (IM column store). This weeks post focuses on how data is accessed within the IM column store. Let’s take a simple query “What is the most expensive air-mail order we have received to date?” SELECT Max(lo_ordtotalprice) most_expensive_order FROM lineorderWHERE  lo_shipmode = 5; The LINEORDER table has been populated into the IM column store and since we have no alternative access paths (indexes or views) the execution plan for this query is a full table scan of the LINEORDER table. You will notice that the execution plan has a new set of keywords “IN MEMORY" in the access method description in the Operation column. These keywords indicate that the LINEORDER table has been marked for INMEMORY and we may use the IM column store in this query. What do I mean by “may use”? There are a small number of cases were we won’t use the IM column store even though the object has been marked INMEMORY. This is similar to how the keyword STORAGE is used on Exadata environments. You can confirm that the IM column store was actually used by examining the session level statistics, but more on that later. For now let's focus on how the data is accessed in the IM column store and why it’s faster to access the data in the new column format, for analytical queries, rather than the buffer cache. There are four main reasons why accessing the data in the IM column store is more efficient. 1. Access only the column data needed The IM column store only has to scan two columns – lo_shipmode and lo_ordtotalprice – to execute this query while the traditional row store or buffer cache has to scan all of the columns in each row of the LINEORDER table until it reaches both the lo_shipmode and the lo_ordtotalprice column. 2. Scan and filter data in it's compressed format When data is populated into the IM column it is automatically compressed using a new set of compression algorithms that allow WHERE clause predicates to be applied against the compressed formats. This means the volume of data scanned in the IM column store for our query will be far less than the same query in the buffer cache where it will scan the data in its uncompressed form, which could be 20X larger. 3. Prune out any unnecessary data within each column The fastest read you can execute is the read you don’t do. In the IM column store a further reduction in the amount of data accessed is possible due to the In-Memory Storage Indexes(IM storage indexes) that are automatically created and maintained on each of the columns in the IM column store. IM storage indexes allow data pruning to occur based on the filter predicates supplied in a SQL statement. An IM storage index keeps track of minimum and maximum values for each column in each of the In-Memory Compression Unit (IMCU). In our query the WHERE clause predicate is on the lo_shipmode column. The IM storage index on the lo_shipdate column is examined to determine if our specified column value 5 exist in any IMCU by comparing the value 5 to the minimum and maximum values maintained in the Storage Index. If the value 5 is outside the minimum and maximum range for an IMCU, the scan of that IMCU is avoided. For the IMCUs where the value 5 does fall within the min, max range, an additional level of data pruning is possible via the metadata dictionary created when dictionary-based compression is used on IMCU. The dictionary contains a list of the unique column values within the IMCU. Since we have an equality predicate we can easily determine if 5 is one of the distinct column values or not. The combination of the IM storage index and dictionary based pruning, enables us to only scan the necessary IMCUs. 4. Use SIMD to apply filter predicates For the IMCU that need to be scanned Oracle takes advantage of SIMD vector processing (Single Instruction processing Multiple Data values). Instead of evaluating each entry in the column one at a time, SIMD vector processing allows a set of column values to be evaluated together in a single CPU instruction. The column format used in the IM column store has been specifically designed to maximize the number of column entries that can be loaded into the vector registers on the CPU and evaluated in a single CPU instruction. SIMD vector processing enables the Oracle Database In-Memory to scan billion of rows per second per core versus the millions of rows per second per core scan rate that can be achieved in the buffer cache. I mentioned earlier in this post that in order to confirm the IM column store was used; we need to examine the session level statistics. You can monitor the session level statistics by querying the performance views v$mystat and v$statname. All of the statistics related to the In-Memory Column Store begin with IM. You can see the full list of these statistics by typing: display_name format a30 SELECT display_name FROM v$statname WHERE  display_name LIKE 'IM%'; If we check the session statistics after we execute our query the results would be as follow; SELECT Max(lo_ordtotalprice) most_expensive_order FROM lineorderWHERE lo_shipmode = 5; SELECT display_name FROM v$statname WHERE  display_name IN ('IM scan CUs columns accessed',                        'IM scan segments minmax eligible',                        'IM scan CUs pruned'); As you can see, only 2 IMCUs were accessed during the scan as the majority of the IMCUs (44) in the LINEORDER table were pruned out thanks to the storage index on the lo_shipmode column. In next weeks post I will describe how you can control which queries use the IM column store and which don't. +Maria Colgan

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  • Unexpected SQL Server 2008 Performance Tip: Avoid local variables in WHERE clause

    - by Jim Duffy
    Sometimes an application needs to have every last drop of performance it can get, others not so much. We’re in the process of converting some legacy Visual FoxPro data into SQL Server 2008 for an application and ran into a situation that required some performance tweaking. I figured the Making Microsoft SQL Server 2008 Fly session that Yavor Angelov (SQL Server Program Manager – Query Processing) presented at PDC 2009 last November would be a good place to start. I was right. One tip among the list of incredibly useful tips Yavor presented was “local variables are bad news for the Query Optimizer and they cause the Query Optimizer to guess”. What that means is you should be avoiding code like this in your stored procs even though it seems such an intuitively good idea. DECLARE @StartDate datetime SET @StartDate = '20091125' SELECT * FROM Orders WHERE OrderDate = @StartDate Instead you should be referencing the value directly in the WHERE clause so the Query Optimizer can create a better execution plan. SELECT * FROM Orders WHERE OrderDate = '20091125' My first thought about this one was we reference variables in the form of passed in parameters in WHERE clauses in many of our stored procs. Not to worry though because parameters ARE available to the Query Optimizer as it compiles the execution plan. I highly recommend checking out Yavor’s session for additional tips to help you squeeze every last drop of performance out of your queries. Have a day. :-|

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  • wired connection not working in ubuntu 12.04 on lenovo G580 laptop

    - by shravankumar
    I found solution in http://www.zyxware.com/articles/2680/solved-wired-connection-eth0-not-detected-in-ubuntu-12-04 I downloaded compact-wireless-2012-07-03-p.tar.bz2 Here the steps i followed along with output 1. shravankumar@shravankumar-Lenovo-G580:~/Desktop/compat-wireless-2012-07-03-p$ scripts/driver-select alx Output: Processing new driver-select request... Backup exists: Makefile.bk Backup exists: Makefile.bk Backup exists: drivers/net/ethernet/broadcom/Makefile.bk Backup exists: drivers/net/ethernet/atheros/Makefile.bk Backup exists: Makefile.bk Backup exists: Makefile.bk Backup exists: drivers/net/ethernet/broadcom/Makefile.bk 2.shravankumar@shravankumar-Lenovo-G580:~/Desktop/compat-wireless-2012-07-03-p$ make output: make -C /lib/modules/3.2.0-23-generic/build M=/home/shravankumar/Desktop/compat-wireless-2012-07-03-p modules make[1]: Entering directory `/usr/src/linux-headers-3.2.0-23-generic' scripts/Makefile.build:44: /home/shravankumar/Desktop/compat-wireless-2012-07-03-p/drivers/net/ethernet/atheros/alx/Makefile: No such file or directory make[4]: *** No rule to make target `/home/shravankumar/Desktop/compat-wireless-2012-07-03-p/drivers/net/ethernet/atheros/alx/Makefile'. Stop. make[3]: *** [/home/shravankumar/Desktop/compat-wireless-2012-07-03-p/drivers/net/ethernet/atheros/alx] Error 2 make[2]: *** [/home/shravankumar/Desktop/compat-wireless-2012-07-03-p/drivers/net/ethernet/atheros] Error 2 make[1]: *** [_module_/home/shravankumar/Desktop/compat-wireless-2012-07-03-p] Error 2 make[1]: Leaving directory `/usr/src/linux-headers-3.2.0-23-generic' make: *** [modules] Error 2 3. hravankumar@shravankumar-Lenovo-G580:~/Desktop/compat-wireless-2012-07-03-p$ make install output: FATAL: Could not open /lib/modules/3.2.0-23-generic/modules.dep.temp for writing: Permission denied make: *** [uninstall] Error 1 4. shravankumar@shravankumar-Lenovo-G580:~/Desktop/compat-wireless-2012-07-03-p$ modeprobe alx output: No command 'modeprobe' found, did you mean: Command 'modprobe' from package 'module-init-tools' (main) modeprobe: command not found I am new to Ubuntu ,Please help me. Thanks in advance

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  • Convert .3GP and .3G2 Files to AVI / MPEG for Free

    - by DigitalGeekery
    3GP and .3G2 are common video capture formats used on many mobile phones, but they may not be supported by your favorite media player. Today we’ll show you a quick and easy way to convert those files to AVI or MPG format with the free Windows application, Pazera Free 3GP to AVI Converter. Download the Pazera Free 3GP to AVI Converter. You’ll have to unzip the download folder, but there is no need to install the application. Just double-click the 3gptoavi.exe file to run the application. To add your 3GP or 3G2 files to the queue to be converted, click on the Add files  button at the top left. Browse for your file, and click Open.   Your video will be added to the Queue. You can add multiple files to the queue and convert them all at one time.   Most users will find it preferable to use one of the pre-configured profiles for their conversion settings. To load a profile, choose one from the Profile drop down list and then click the Load button. You will see the profile update the settings in the panels at the bottom of the application. We tested Pazera Free 3GP to AVI Converter with 3GP files recorded on a Motorola Droid, and found the AVI H.264 Very High Q. profile to return the best results for AVI output, and the MPG – DVD NTSC: MPEG-2 the best results for MPG output. Other profiles produced smaller file sizes, but at a cost of reduced quality video output.   More advanced users may tweak video and audio settings to their liking in the lower panels. Click on the AVI button under Output file format / Video settings to adjust settings AVI… Or the MPG button to adjust the settings for MPG output. By default, the converted file will be output to the same location as the input directory. You can change it by clicking the text box input radio button and browsing for a different folder. When you’ve chosen your settings, click Convert to begin the conversion process.   A conversion output box will open and display the progress. When finished, click Close. Now you’re ready to enjoy your video in your favorite media player. Pazera Free 3GP to AVI Converter isn’t the most robust media conversion tool, but it does what it is intended to do. It handles the task of 3GP to AVI / MPG conversion very well. It’s easy enough for the beginner to manage without much trouble, but also has enough options to please more experienced users. Download Pazera Free 3GP to AVI Converter Similar Articles Productive Geek Tips How To Convert Video Files to MP3 with VLCEasily Change Audio File Formats with XRECODEConvert PDF Files to Word Documents and Other FormatsConvert Video and Remove Commercials in Windows 7 Media Center with MCEBuddy 1.1Compress Large Video Files with DivX / Xvid and AutoGK TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 Install, Remove and HIDE Fonts in Windows 7 Need Help with Your Home Network? Awesome Lyrics Finder for Winamp & Windows Media Player Download Videos from Hulu Pixels invade Manhattan Convert PDF files to ePub to read on your iPad

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  • What version of webcenter do I have?

    - by angelo.santagata
    Ive seen this come up a few times, someone has webcenter installed, but isnt sure *exactly* which version of webcenter 11g they have installed.. Well its quite easy... Connect to sqplus as SYSDBA to the WebCenter database Run the following query to get the WebCenter schema: select username from all_users where username like '%WEBCENTER%'; Take note of the WebCenter username so you can use in next query. Run the following query to get the WebCenter version: Replace: - With the username from previous query. select version from .WC_REPOSITORY_VERSION; Also worth noting this is all documented in support note Note 1053606.1 available at metalink

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  • Slow IE8 Start-up due to LDAP DNS queries

    - by MikeJ-UK
    Recently (in the last few days), my installation of IE8 has been taking 15 to 20 seconds to load my home page. Specifically, the sequence of events (as reported by WireShark) is:- Browser issues a DNS A query to resolve the home page server's IP address. Browser then spends the next 15-20 seconds broadcasting DNS SRV _LDAP._TCP queries, (roughly on a 2 second tick) to which it receives no answer (we have no LDAP servers). Browser re-issues the DNS A query and resolves the server's IP address again. Finally, the browser issues an HTTP GET for the home page. Does anyone know why this is happening? Possibly related to this question EDIT: @Massimo, LDAP query is :- Domain Name System (query) Transaction ID: 0x11c5 Flags: 0x0100 (Standard query) Questions: 1 Answer RRS: 0 Authority RRS: 0 Additional RRS: 0 Queries _LDAP._TCP: type SRV, class IN Name: _LDAP._TCP Type: SRV (Service location) Class: IN (0x0001)

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  • Sub routing in a SPA site

    - by Anders
    I have a SPA site that I'm working on, I have a requirement that you can have subroutes for a page view model. Im currently using this 'pattern' for the site MyApp.FooViewModel = MyApp.define({ meta: { query: MyApp.Core.Contracts.Queries.FooQuery, title: "Foo" }, init: function (queryResult) { }, prototype: { } }); In the master view model I have a route table this.navigation(new MyApp.RoutesViewModel({ Home: { model: MyApp.HomeViewModel, route: String.empty }, Foo: { model: MyApp.FooViewModel } })); The meta object defines which query should populate the top level view model when its invoked through sammyjs, this is all fine but it does not support sub routing My plan is to change the meta object so that it can (optional offcourse) look like this meta: { query: MyApp.Core.Contracts.Queries.FooQuery, title: "Foo", route: { barId: MyApp.BarViewModel } } When sammyjs detects a barId in the query string the Barmodel will be executed and populated through its own meta object. Is this a good design?

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  • Squid closing the connection on long HTTP GET requests

    - by Rhys
    Hello, When running a database query on a specific external site we use, Squid seems to cut off the connection after a consistent period of time (just over a minute). The query is submitted through a standard web form is that uses GET to query their database. Firefox 3 just displays a blank page. Internet Explorer throws a 'Page Cannot Be Displayed' error (tested in v6 and v8). When we perform the same query on the same machine, but bypass the Squid proxy, it works fine. The query takes about two and a half minutes to complete. There are a few timeout settings in Squid, but I honestly don't know what one to be looking at. Any possible solutions would be much appreciated. Cheers

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  • A tale from a Stalker

    - by Peter Larsson
    Today I thought I should write something about a stalker I've got. Don't get me wrong, I have way more fans than stalkers, but this stalker is particular persistent towards me. It all started when I wrote about Relational Division with Sets late last year(http://weblogs.sqlteam.com/peterl/archive/2010/07/02/Proper-Relational-Division-With-Sets.aspx) and no matter what he tried, he didn't get a better performing query than me. But this I didn't click until later into this conversation. He must have saved himself for 9 months before posting to me again. Well... Some days ago I get an email from someone I thought i didn't know. Here is his first email Hi, I want a proper solution for achievement the result. The solution must be standard query, means no using as any native code like TOP clause, also the query should run in SQL Server 2000 (no CTE use). We have a table with consecutive keys (nbr) that is not exact sequence. We need bringing all values related with nearest key in the current key row. See the DDL: CREATE TABLE Nums(nbr INTEGER NOT NULL PRIMARY KEY, val INTEGER NOT NULL); INSERT INTO Nums(nbr, val) VALUES (1, 0),(5, 7),(9, 4); See the Result: pre_nbr     pre_val     nbr         val         nxt_nbr     nxt_val ----------- ----------- ----------- ----------- ----------- ----------- NULL        NULL        1           0           5           7 1           0           5           7           9           4 5           7           9           4           NULL        NULL The goal is suggesting most elegant solution. I would like see your best solution first, after that I will send my best (if not same with yours)   Notice there is no name, no please or nothing polite asking for my help. So, on the top of my head I sent him two solutions, following the rule "Work on SQL Server 2000 and only standard non-native code".     -- Peso 1 SELECT               pre_nbr,                              (                                                           SELECT               x.val                                                           FROM                dbo.Nums AS x                                                           WHERE              x.nbr = d.pre_nbr                              ) AS pre_val,                              d.nbr,                              d.val,                              d.nxt_nbr,                              (                                                           SELECT               x.val                                                           FROM                dbo.Nums AS x                                                           WHERE              x.nbr = d.nxt_nbr                              ) AS nxt_val FROM                (                                                           SELECT               (                                                                                                                     SELECT               MAX(x.nbr) AS nbr                                                                                                                     FROM                dbo.Nums AS x                                                                                                                     WHERE              x.nbr < n.nbr                                                                                        ) AS pre_nbr,                                                                                        n.nbr,                                                                                        n.val,                                                                                        (                                                                                                                     SELECT               MIN(x.nbr) AS nbr                                                                                                                     FROM                dbo.Nums AS x                                                                                                                     WHERE              x.nbr > n.nbr                                                                                        ) AS nxt_nbr                                                           FROM                dbo.Nums AS n                              ) AS d -- Peso 2 CREATE TABLE #Temp                                                         (                                                                                        ID INT IDENTITY(1, 1) PRIMARY KEY,                                                                                        nbr INT,                                                                                        val INT                                                           )   INSERT                                            #Temp                                                           (                                                                                        nbr,                                                                                        val                                                           ) SELECT                                            nbr,                                                           val FROM                                             dbo.Nums ORDER BY         nbr   SELECT                                            pre.nbr AS pre_nbr,                                                           pre.val AS pre_val,                                                           t.nbr,                                                           t.val,                                                           nxt.nbr AS nxt_nbr,                                                           nxt.val AS nxt_val FROM                                             #Temp AS pre RIGHT JOIN      #Temp AS t ON t.ID = pre.ID + 1 LEFT JOIN         #Temp AS nxt ON nxt.ID = t.ID + 1   DROP TABLE    #Temp Notice there are no indexes on #Temp table yet. And here is where the conversation derailed. First I got this response back Now my solutions: --My 1st Slt SELECT T2.*, T1.*, T3.*   FROM Nums AS T1        LEFT JOIN Nums AS T2          ON T2.nbr = (SELECT MAX(nbr)                         FROM Nums                        WHERE nbr < T1.nbr)        LEFT JOIN Nums AS T3          ON T3.nbr = (SELECT MIN(nbr)                         FROM Nums                        WHERE nbr > T1.nbr); --My 2nd Slt SELECT MAX(CASE WHEN N1.nbr > N2.nbr THEN N2.nbr ELSE NULL END) AS pre_nbr,        (SELECT val FROM Nums WHERE nbr = MAX(CASE WHEN N1.nbr > N2.nbr THEN N2.nbr ELSE NULL END)) AS pre_val,        N1.nbr AS cur_nbr, N1.val AS cur_val,        MIN(CASE WHEN N1.nbr < N2.nbr THEN N2.nbr ELSE NULL END) AS nxt_nbr,        (SELECT val FROM Nums WHERE nbr = MIN(CASE WHEN N1.nbr < N2.nbr THEN N2.nbr ELSE NULL END)) AS nxt_val   FROM Nums AS N1,        Nums AS N2  GROUP BY N1.nbr, N1.val;   /* My 1st Slt Table 'Nums'. Scan count 7, logical reads 14 My 2nd Slt Table 'Nums'. Scan count 4, logical reads 23 Peso 1 Table 'Nums'. Scan count 9, logical reads 28 Peso 2 Table '#Temp'. Scan count 0, logical reads 7 Table 'Nums'. Scan count 1, logical reads 2 Table '#Temp'. Scan count 3, logical reads 16 */  To this, I emailed him back asking for a scalability test What if you try with a Nums table with 100,000 rows? His response to that started to get nasty.  I have to say Peso 2 is not acceptable. As I said before the solution must be standard, ORDER BY is not part of standard SELECT. Try this without ORDER BY:  Truncate Table Nums INSERT INTO Nums (nbr, val) VALUES (1, 0),(9,4), (5, 7)  So now we have new rules. No ORDER BY because it's not standard SQL! Of course I asked him  Why do you have that idea? ORDER BY is not standard? To this, his replies went stranger and stranger Standard Select = Set-based (no any cursor) It’s free to know, just refer to Advanced SQL Programming by Celko or mail to him if you accept comments from him. What the stalker probably doesn't know, is that I and Mr Celko occasionally are involved in some conversation and thus we exchange emails. I don't know if this reference to Mr Celko was made to intimidate me either. So I answered him, still polite, this What do you mean? The SELECT itself has a ”cursor under the hood”. Now the stalker gets rude  But however I mean the solution must no containing any order by, top... No problem, I do not like Peso 2, it’s very non-intelligent and elementary. Yes, Peso 2 is elementary but most performing queries are... And now is the time where I started to feel the stalker really wanted to achieve something else, so I wrote to him So what is your goal? Have a query that performs well, or a query that is super-portable? My Peso 2 outperforms any of your code with a factor of 100 when using more than 100,000 rows. While I awaited his answer, I posted him this query Ok, here is another one -- Peso 3 SELECT             MAX(CASE WHEN d = 1 THEN nbr ELSE NULL END) AS pre_nbr,                    MAX(CASE WHEN d = 1 THEN val ELSE NULL END) AS pre_val,                    MAX(CASE WHEN d = 0 THEN nbr ELSE NULL END) AS nbr,                    MAX(CASE WHEN d = 0 THEN val ELSE NULL END) AS val,                    MAX(CASE WHEN d = -1 THEN nbr ELSE NULL END) AS nxt_nbr,                    MAX(CASE WHEN d = -1 THEN val ELSE NULL END) AS nxt_val FROM               (                              SELECT    nbr,                                        val,                                        ROW_NUMBER() OVER (ORDER BY nbr) AS SeqID                              FROM      dbo.Nums                    ) AS s CROSS JOIN         (                              VALUES    (-1),                                        (0),                                        (1)                    ) AS x(d) GROUP BY           SeqID + x.d HAVING             COUNT(*) > 1 And here is the stats Table 'Nums'. Scan count 1, logical reads 2, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. It beats the hell out of your queries…. Now I finally got a response from my stalker and now I also clicked who he was. This is his reponse Why you post my original method with a bit change under you name? I do not like it. See: http://www.sqlservercentral.com/Forums/Topic468501-362-14.aspx ;WITH C AS ( SELECT seq_nbr, k,        DENSE_RANK() OVER(ORDER BY seq_nbr ASC) + k AS grp_fct   FROM [Sample]         CROSS JOIN         (VALUES (-1), (0), (1)         ) AS D(k) ) SELECT MIN(seq_nbr) AS pre_value,        MAX(CASE WHEN k = 0 THEN seq_nbr END) AS current_value,        MAX(seq_nbr) AS next_value   FROM C GROUP BY grp_fct HAVING min(seq_nbr) < max(seq_nbr); These posts: Posted Tuesday, April 12, 2011 10:04 AM Posted Tuesday, April 12, 2011 1:22 PM Why post a solution where will not work in SQL Server 2000? Wait a minute! His own solution is using both a CTE and a ranking function so his query will not work on SQL Server 2000! Bummer... The reference to "Me not like" are my exact words in a previous topic on SQLTeam.com and when I remembered the phrasing, I also knew who he was. See this topic http://www.sqlteam.com/forums/topic.asp?TOPIC_ID=159262 where he writes a query and posts it under my name, as if I wrote it. So I answered him this (less polite). Like I keep track of all topics in the whole world… J So you think you are the only one coming up with this idea? Besides, “M S solution” doesn’t work.   This is the result I get pre_value        current_value                             next_value 1                           1                           5 1                           5                           9 5                           9                           9   And I did nothing like you did here, where you posted a solution which you “thought” I should write http://www.sqlteam.com/forums/topic.asp?TOPIC_ID=159262 So why are you yourself using ranking function when this was not allowed per your original email, and no cte? You use CTE in your link above, which do not work in SQL Server 2000. All this makes no sense to me, other than you are trying your best to once in a lifetime create a better performing query than me? After a few hours I get this email back. I don't fully understand it, but it's probably a language barrier. >>Like I keep track of all topics in the whole world… J So you think you are the only one coming up with this idea?<< You right, but do not think you are the first creator of this.   >>Besides, “M S Solution” doesn’t work. This is the result I get <<   Why you get so unimportant mistake? See this post to correct it: Posted 4/12/2011 8:22:23 PM >> So why are you yourself using ranking function when this was not allowed per your original email, and no cte? You use CTE in your link above, which do not work in SQL Server 2000. <<  Again, why you get some unimportant incompatibility? You offer that solution for current goals not me  >> All this makes no sense to me, other than you are trying your best to once in a lifetime create a better performing query than me? <<  No, I only wanted to know who you will solve it. Now I know you do not have a special solution. No problem. No problem for me either. So I just answered him I am not the first, and you are not the first to come up with this idea. So what is your problem? I am pretty sure other people have come up with the same idea before us. I used this technique all the way back to 2007, see http://www.sqlteam.com/forums/topic.asp?TOPIC_ID=93911 Let's see if he returns...  He did! >> So what is your problem? << Nothing Thanks for all replies; maybe we have some competitions in future, maybe. Also I like you but you do not attend it. Your behavior with me is not friendly. Not any meeting… Regards //Peso

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  • What's the best practice for async APIs that return futures on Scala?

    - by Maurício Linhares
    I have started a project to write an async PostgreSQL driver on Scala and to be async, I need to accept callbacks and use futures, but then accepting a callback and a future makes the code cumbersome because you always have to send a callback even if it is useless. Here's a test: "insert a row in the database" in { withHandler { (handler, future) => future.get(5, TimeUnit.SECONDS) handler.sendQuery( this.create ){ query => }.get( 5, TimeUnit.SECONDS ) handler.sendQuery( this.insert ){ query => }.get( 5, TimeUnit.SECONDS ).rowsAffected === 1 } } Sending the empty callback is horrible but I couldn't find a way to make it optional or anything like that, so right now I don't have a lot of ideas on how this external API should look like. It could be something like: handler.sendQuery( this.create ).addListener { query => println(query) } But then again, I'm not sure how people are organizing API's in this regard. Providing examples in other projects would also be great.

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  • Secret of SQL Trace Duration Column

    - by Dan Guzman
    Why would a trace of long-running queries not show all queries that exceeded the specified duration filter?  We have a server-side SQL Trace that includes RPC:Completed and SQL:BatchCompleted events with a filter on Duration >= 100000.  Nearly all of the queries on this busy OLTP server run in under this 100 millisecond threshold so any that appear in the trace are candidates for root cause analysis and/or performance tuning opportunities. After an application experienced query timeouts, the DBA looked at the trace data to corroborate the problem.  Surprisingly, he found no long-running queries in the trace from the application that experienced the timeouts even though the application’s error log clearly showed detail of the problem (query text, duration, start time, etc.).  The trace did show, however, that there were hundreds of other long-running queries from different applications during the problem timeframe.  We later determined those queries were blocked by a large UPDATE query against a critical table that was inadvertently run during this busy period. So why didn’t the trace include all of the long-running queries?  The reason is because the SQL Trace event duration doesn’t include the time a request was queued while awaiting a worker thread.  Remember that the server was under considerable stress at the time due to the severe blocking episode.  Most of the worker threads were in use by blocked queries and new requests were queued awaiting a worker to free up (a DMV query on the DAC connection will show this queuing: “SELECT scheduler_id, work_queue_count FROM sys.dm_os_schedulers;”).  Technically, those queued requests had not started.  As worker threads became available, queries were dequeued and completed quickly.  These weren’t included in the trace because the duration was under the 100ms duration filter.  The duration reflected the time it took to actually run the query but didn’t include the time queued waiting for a worker thread. The important point here is that duration is not end-to-end response time.  Duration of RPC:Completed and SQL:BatchCompleted events doesn’t include time before a worker thread is assigned nor does it include the time required to return the last result buffer to the client.  In other words, duration only includes time after the worker thread is assigned until the last buffer is filled.  But be aware that duration does include the time need to return intermediate result set buffers back to the client, which is a factor when large query results are returned.  Clients that are slow in consuming results sets can increase the duration value reported by the trace “completed” events.

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  • Max Degree of Parallelism Server-Side Setting

    - by Tara Kizer
    Recently I opened a case with Microsoft PSS to help us through a severe performance problem on a new system.  As part of that case, the PSS engineer checked our “max degree of parallelism” server-side setting.  It is our standard to use 4 on our production systems that have 16 CPUs (2 sockets, quad-core, hyper-threaded).  The PSS engineer had me run the below query to get Microsoft’s recommended value of “max degree of parallelism” server-side setting for our 16-CPU system: select case when cpu_count / hyperthread_ratio > 8 then 8 else cpu_count / hyperthread_ratio end as optimal_maxdop_setting from sys.dm_os_sys_info; The query returned 2.  I made the change using sp_configure, and it did not resolve our issue.  We have decided to leave it in place for now.   Do you agree with this query?  What are your thoughts on this? If you decide to change your setting to reflect the output of this query, please test it first to ensure there are no negative side effects.

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  • Help with "Cannot find ContentTypeReader BB.HeightMapInfoReader, BB, Version=1.0.0.0, Culture=neutral." needed

    - by rFactor
    Hi, I have this irritating problem in XNA that I have spent my Saturday with: Cannot find ContentTypeReader BB.HeightMapInfoReader, BB, Version=1.0.0.0, Culture=neutral. It throws me that when I do (within the game assembly's Renderer.cs class): this.terrain = this.game.Content.Load<Model>("heightmap"); There is a heightmap.bmp and I don't think there's anything wrong with it, because I used it in a previous version which I switched to this new better system. So, I have a GeneratedGeometryPipeline assembly that has these classes: HeightMapInfoContent, HeightMapInfoWriter, TerrainProcessor. The GeneratedGeometryPipeline assembly does not reference any other assemblies under the solution. Then I have the game assembly that neither references any other solution assemblies and has these classes: HeightMapInfo, HeightMapInfoReader. All game assembly classes are under namespace BB and the GeneratedGeometryPipeline classes are under the namespace GeneratedGeometryPipeline. I do not understand why it does not find it. Here's some code from the GeneratedGeometryPipeline.HeightMapInfoWriter: /// <summary> /// A TypeWriter for HeightMapInfo, which tells the content pipeline how to save the /// data in HeightMapInfo. This class should match HeightMapInfoReader: whatever the /// writer writes, the reader should read. /// </summary> [ContentTypeWriter] public class HeightMapInfoWriter : ContentTypeWriter<HeightMapInfoContent> { protected override void Write(ContentWriter output, HeightMapInfoContent value) { output.Write(value.TerrainScale); output.Write(value.Height.GetLength(0)); output.Write(value.Height.GetLength(1)); foreach (float height in value.Height) { output.Write(height); } foreach (Vector3 normal in value.Normals) { output.Write(normal); } } /// <summary> /// Tells the content pipeline what CLR type the /// data will be loaded into at runtime. /// </summary> public override string GetRuntimeType(TargetPlatform targetPlatform) { return "BB.HeightMapInfo, BB, Version=1.0.0.0, Culture=neutral"; } /// <summary> /// Tells the content pipeline what worker type /// will be used to load the data. /// </summary> public override string GetRuntimeReader(TargetPlatform targetPlatform) { return "BB.HeightMapInfoReader, BB, Version=1.0.0.0, Culture=neutral"; } } Can someone help me out?

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  • Execution plan different on two different Sql Servers

    - by Lieven Cardoen
    On our sql server, a query takes 20 ms. If I look at the execution plan, parallelism is used, hash match, Bitmap create, ... a lot of images with two arrows pointing to the left. On sql server of a customer where our product runs, the same query takes 2500 ms. If I look at their execution plan, no parallelism or any of the things with arrows are used... I've been searching for a couple of days no why the query runs so much slower on their sql server. Is parallelism and all of the other things something that can be configured on their sql server? And how to you configure that? What are the dangers of using parallelism? Another strange thing is that on our server, the query needs some 1200 reads and 0 writes. On their sql server it needs 1.5 million reads and some 1500 writes. Why these writes when a read query is done?

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  • Checking for cross-site scripting vulnerabilities in Perl web applications

    - by David Scholefield
    I'm putting together some notes for a dev team on how to write secure Perl code - especially taking into account the current OWASP top 10 web application vulnerabilities. For cross-site scripting I've included information on ensuring that all output to the browser is checked and escaped where necessary, but I'm looking for more automated mechanisms that would mean a developer doesn't have to think about every output statement and, potentially, miss one. Perl's 'taint' function sounds like it should be a help because it distrusts all user input, but it doesn't complain on tainted data being output to the browser. Apart from checking all output statements individually (probably by calling a generic sanitizing function) does anyone have any ideas on how Perl can help with this with existing libraries or techniques?

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  • SQL Server 2008 Optimization

    - by hgulyan
    I've learned today, if you append to your query OPTION (MAXDOP 0) your query will run on multiple processors and if it's huge query, query will perform faster. I know general guidelines on query optimizations (using indexes, selecting only needed fields etc.), my question is about SQL Server optimization. Maybe changing some options in configurations or anything else. What guidelines are there for SQL Server Optimization? Thank you. P.S. I suppose, this is not the right place to ask server related questions. Should I delete it or maybe it can be migrated to serverfault?

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  • bash disable line wrap without truncation

    - by Eric Huang
    I am using a template heavy library in c++ and need to understand the template errors. Reading line wrapped template errors is a serious pain. Is there a way to disable line wrapping in bash without also truncating the output. Additionally, is there a way to do horizontal scrolling on the output. I have seen this answer, how to make bash not to wrap output?, but the output is truncated. The solution doesn't have to be bash targeted, if there is method for this using another shell, tmux, piping make output to another program, compiling from within vim, etc, I'll use it. (Except for copy-pasting into gedit)

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  • Upgrade won't allow second display to go to 1920x1080

    - by Rick
    I just upgraded to 10.10 last night and I'm having issues now with dual display from my laptop dock. This was working in the previous release with a manual xrandr command: xrandr --output LVDS1 --off --output DP1 --mode 1920x1080 && xrandr --output VGA1 --mode 1920x1080 --left-of DP1 When I run this now, the DP1 output doesn't have a mode for 1920x1080. The two displays are a matched pair of dell 22" that are both 1920x1080. When I attempt to manually add the mode xrandr --addmode DP1 1920x1080 and rerun my command, I lose both displays altogether. I have to then blindly reset to just one of them in order to get display back. If I avoid the 1920 and just attempt to setup DP1 at the 1280x1024 max it thinks it has, then the second display will come up, but obviously looks horrible since it's non-native resolution. I've grabbed the updated xorg intel driver from the stable X ppa and am running: 2:2.13.901-2ubuntu2~xup~maverick xrandr output Screen 0: minimum 320 x 200, current 1920 x 1080, maximum 8192 x 8192 VGA1 connected 1920x1080+0+0 (normal left inverted right x axis y axis) 477mm x 268mm 1920x1080 60.0*+ 1280x1024 75.0 60.0 1152x864 75.0 1024x768 75.1 60.0 800x600 75.0 60.3 640x480 75.0 60.0 720x400 70.1 LVDS1 connected (normal left inverted right x axis y axis) 1280x800 60.2 + 1024x768 60.0 800x600 60.3 56.2 640x480 59.9 HDMI1 disconnected (normal left inverted right x axis y axis) DP1 connected (normal left inverted right x axis y axis) 1280x1024 75.0 60.0 1152x864 75.0 1024x768 75.1 60.0 800x600 75.0 60.3 640x480 75.0 60.0 720x400 70.1

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  • Checking who is connected to your server, with PowerShell.

    - by Fatherjack
    There are many occasions when, as a DBA, you want to see who is connected to your SQL Server, along with how they are connecting and what sort of activities they are carrying out. I’m going to look at a couple of ways of getting this information and compare the effort required and the results achieved of each. SQL Server comes with a couple of stored procedures to help with this sort of task – sp_who and its undocumented counterpart sp_who2. There is also the pumped up version of these called sp_whoisactive, written by Adam Machanic which does way more than these procedures. I wholly recommend you try it out if you don’t already know how it works. When it comes to serious interrogation of your SQL Server activity then it is absolutely indispensable. Anyway, back to the point of this blog, we are going to look at getting the information from sp_who2 for a remote server. I wrote this Powershell script a week or so ago and was quietly happy with it for a while. I’m relatively new to Powershell so forgive both my rather low threshold for entertainment and the fact that something so simple is a moderate achievement for me. $Server = 'SERVERNAME' $SMOServer = New-Object Microsoft.SQLServer.Management.SMO.Server $Server # connection and query stuff         $ConnectionStr = "Server=$Server;Database=Master;Integrated Security=True" $Query = "EXEC sp_who2" $Connection = new-object system.Data.SQLClient.SQLConnection $Table = new-object "System.Data.DataTable" $Connection.connectionstring = $ConnectionStr try{ $Connection.open() $Command = $Connection.CreateCommand() $Command.commandtext = $Query $result = $Command.ExecuteReader() $Table.Load($result) } catch{ # Show error $error[0] | format-list -Force } $Title = "Data access processes (" + $Table.Rows.Count + ")" $Table | Out-GridView -Title $Title $Connection.close() So this is pretty straightforward, create an SMO object that represents our chosen server, define a connection to the database and a table object for the results when we get them, execute our query over the connection, load the results into our table object and then, if everything is error free display these results to the PowerShell grid viewer. The query simply gets the results of ‘EXEC sp_who2′ for us. Depending on how many connections there are will influence how long the query runs. The grid viewer lets me sort and search the results so it can be a pretty handy way to locate troublesome connections. Like I say, I was quite pleased with this, it seems a pretty simple script and was working well for me, I have added a few parameters to control the output and give me more specific details but then I see a script that uses the $SMOServer object itself to provide the process information and saves having to define the connection object and query specifications. $Server = 'SERVERNAME' $SMOServer = New-Object Microsoft.SQLServer.Management.SMO.Server $Server $Processes = $SMOServer.EnumProcesses() $Title = "SMO processes (" + $Processes.Rows.Count + ")" $Processes | Out-GridView -Title $Title Create the SMO object of our server and then call the EnumProcesses method to get all the process information from the server. Staggeringly simple! The results are a little different though. Some columns are the same and we can see the same basic information so my first thought was to which runs faster – so that I can get my results more quickly and also so that I place less stress on my server(s). PowerShell comes with a great way of testing this – the Measure-Command function. All you have to do is wrap your piece of code in Measure-Command {[your code here]} and it will spit out the time taken to execute the code. So, I placed both of the above methods of getting SQL Server process connections in two Measure-Command wrappers and pressed F5! The Powershell console goes blank for a while as the code is executed internally when Measure-Command is used but the grid viewer windows appear and the console shows this. You can take the output from Measure-Command and format it for easier reading but in a simple comparison like this we can simply cross refer the TotalMilliseconds values from the two result sets to see how the two methods performed. The query execution method (running EXEC sp_who2 ) is the first set of timings and the SMO EnumProcesses is the second. I have run these on a variety of servers and while the results vary from execution to execution I have never seen the SMO version slower than the other. The difference has varied and the time for both has ranged from sub-second as we see above to almost 5 seconds on other systems. This difference, I would suggest is partly due to the cost overhead of having to construct the data connection and so on where as the SMO EnumProcesses method has the connection to the server already in place and just needs to call back the process information. There is also the difference in the data sets to consider. Let’s take a look at what we get and where the two methods differ Query execution method (sp_who2) SMO EnumProcesses Description - Urn What looks like an XML or JSON representation of the server name and the process ID SPID Spid The process ID Status Status The status of the process Login Login The login name of the user executing the command HostName Host The name of the computer where the  process originated BlkBy BlockingSpid The SPID of a process that is blocking this one DBName Database The database that this process is connected to Command Command The type of command that is executing CPUTime Cpu The CPU activity related to this process DiskIO - The Disk IO activity related to this process LastBatch - The time the last batch was executed from this process. ProgramName Program The application that is facilitating the process connection to the SQL Server. SPID1 - In my experience this is always the same value as SPID. REQUESTID - In my experience this is always 0 - Name In my experience this is always the same value as SPID and so could be seen as analogous to SPID1 from sp_who2 - MemUsage An indication of the memory used by this process but I don’t know what it is measured in (bytes, Kb, Mb…) - IsSystem True or False depending on whether the process is internal to the SQL Server instance or has been created by an external connection requesting data. - ExecutionContextID In my experience this is always 0 so could be analogous to REQUESTID from sp_who2. Please note, these are my own very brief descriptions of these columns, detail can be found from MSDN for columns in the sp_who results here http://msdn.microsoft.com/en-GB/library/ms174313.aspx. Where the columns are common then I would use that description, in other cases then the information returned is purely for interpretation by the reader. Rather annoyingly both result sets have useful information that the other doesn’t. sp_who2 returns Disk IO and LastBatch information which is really useful but the SMO processes method give you IsSystem and MemUsage which have their place in fault diagnosis methods too. So which is better? On reflection I think I prefer to use the sp_who2 method primarily but knowing that the SMO Enumprocesses method is there when I need it is really useful and I’m sure I’ll use it regularly. I’m OK with the fact that it is the slower method because Measure-Command has shown me how close it is to the other option and that it really isn’t a large enough margin to matter.

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  • How does a search functionality fit in DDD with CQRS?

    - by Songo
    In Vaughn Vernon's book Implementing domain driven design and the accompanying sample application I found that he implemented a CQRS approach to the iddd_collaboration bounded context. He presents the following classes in the application service layer: CalendarApplicationService.java CalendarEntryApplicationService.java CalendarEntryQueryService.java CalendarQueryService.java I'm interested to know if an application will have a search page that feature numerous drop downs and check boxes with a smart text box to match different search patterns; How will you structure all that search logic? In a command service or a query service? Taking a look at the CalendarQueryService.java I can see that it has 2 methods for a huge query, but no logic at all to mix and match any search filters for example. I've heard that the application layer shouldn't have any business logic, so where will I construct my dynamic query? or maybe just clutter everything in the Query service?

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  • PostgreSQL data diff

    - by skanatek
    Note: this question is not about syncing database schema/structure Problem In my web application I have a PostgreSQL database server (PGS) and a (separate machine) business logic server (BLS) which regularly (every minute or two) queries 'SELECT ALL' against PGS. The problem is that the 'SELECT ALL' query can easily return 50-200 MB each time. It is obvious that it would be not so good architecture-wise to transfer so much data so frequently over the web. Possible solution What I would like to do is to run some diff tool on PGS and compare the new query with the previous query (all this should be done on PGS). Once the comparison is done I would like to get a dump from PGS and transfer it to BLS. I expect that a diff-based dump would be much, much smaller than the whole 'SELECT ALL' query. Question Is there any data diff tool for PostgreSQL that can do diffs that compare PostgreSQL data between 2 tables or 2 dumps? Note: I would prefer some open-source software tool.

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