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  • Drupal rest services in Json format

    - by Sreekanth Chandrabhatla
    Amworking on drupal 7. Created a rest services in drupal views. I want to consume this service in my android app. When i try to view my service http://mysite.com/ubercart/?q=doctor am getting response like this [{,"foaf:Document"],"title":{"predicates":["dc:title"]},"created":{"predicates":["dc:date","dc:created"],"datatype":"xsd:dateTime","callback":"date_iso8601"},"changed":{"predicates":["dc:modified"],"datatype":"xsd:dateTime","callback":"date_iso8601"},"body":{"predicates":[""vid":"12","uid":"1","title":"raja","log":"","status":"1","comment":"2","promote":"0","sticky":"0","nid":"12","type":"doctor","language":"und","created":"1351849158","changed":"1351849158","tnid":"0","translate":"0","revision_timestamp":"1351849158","revision_uid":"1","field_rating":{"und":[{"value":"4"}]},"field_place":{"und":[{"value":"Guntur","format":null,"safe_value":"Guntur"}]},"rdf_mapping":{"rdftype":["sioc:Item","foaf:Document"],"title":{"predicates":["dc:title"]},"created":{"predicates":["dc:date","dc:created"],"datatype":"xsd:dateTime","callback":"date_iso8601"},"changed":{"predicates":["dc:modified"],"datatype":"xsd:dateTime","callback":"date_iso8601"},"body":{"predicates":["content:encoded"]},"uid":{"predicates":["sioc:has_creator"],"type":"rel"},"name":{"predicates":["foaf:name"]},"comment_count":{"predicates":["sioc:num_replies"],"datatype":"xsd:integer"},"last_activity":{"predicates":["sioc:last_activity_date"],"datatype":"xsd:dateTime","callback":"date_iso8601"}},"cid":"0","last_comment_timestamp":"1351849158","last_comment_name":null,"last_comment_uid":"1","comment_count":"0","name":"admin","picture":"0","data":"b:0;","uc_order_product_id":false,"ucnc_product_nid":false},{"vid":"11","uid":"1","title":"ravi","log":"","status":"1","comment":"2","promote":"0","sticky":"0","nid":"11","type":"doctor","language":"und","created":"1351849131","changed":"1351849131","tnid":"0","translate":"0","revision_timestamp":"1351849131","revision_uid":"1","field_rating":{"und":[{"value":"5"}]},"field_place":{"und":[{"value":"Hyderabad","format":null,"safe_value":"Hyderabad"}]},"rdf_mapping":{"rdftype":["sioc:Item","foaf:Document"],"title":{"predicates":["dc:title"]},"created":{"predicates":["dc:date","dc:created"],"datatype":"xsd:dateTime","callback":"date_iso8601"},"changed":{"predicates":["dc:modified"],"datatype":"xsd:dateTime","callback":"date_iso8601"},"body":{"predicates":["content:encoded"]},"uid":{"predicates":["sioc:has_creator"],"type":"rel"},"name":{"predicates":["foaf:name"]},"comment_count":{"predicates":["sioc:num_replies"],"datatype":"xsd:integer"},"last_activity":{"predicates":["sioc:last_activity_date"],"datatype":"xsd:dateTime","callback":"date_iso8601"}},"cid":"0","last_comment_timestamp":"1351849131","last_comment_name":null,"last_comment_uid":"1","comment_count":"0","name":"admin","picture":"0","data":"b:0;","uc_order_product_id":false,"ucnc_product_nid":false},{"vid":"10","uid":"1","title":"sree","log":"","status":"1","comment":"2","promote":"0","sticky":"0","nid":"10","type":"doctor","language":"und","created":"1351849109","changed":"1351849109","tnid":"0","translate":"0","revision_timestamp":"1351849109","revision_uid":"1","field_rating":{"und":[{"value":"4"}]},"field_place":{"und":[{"value":"Hyderabad","format":null,"safe_value":"Hyderabad"}]},"rdf_mapping":{"rdftype":["sioc:Item"content:encoded"]},"uid":{"predicates":["sioc:has_creator"],"type":"rel"},"name":{"predicates":["foaf:name"]},"comment_count":{"predicates":["sioc:num_replies"],"datatype":"xsd:integer"},"last_activity":{"predicates":["sioc:last_activity_date"],"datatype":"xsd:dateTime","callback":"date_iso8601"}},"cid":"0","last_comment_timestamp":"1351849109","last_comment_name":null,"last_comment_uid":"1","comment_count":"0","name":"admin","picture":"0","data":"b:0;","uc_order_product_id":false,"ucnc_product_nid":false}] Actually i need response like this {"nodes":{"0":{"node":{"title":"raja","field_place":"Guntur","rating":"4"}},"1":{"node":{"title":"ravi","field_place":"Hyderabad","rating":"5"}},"2":{"node":{"title":"sree","field_place":"Hyderabad","rating":"4"}}}} Do any one can me out?

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  • An XEvent a Day (14 of 31) – A Closer Look at Predicates

    - by Jonathan Kehayias
    When working with SQL Trace, one of my biggest frustrations has been the limitations that exist in filtering.  Using sp_trace_setfilter to establish the filter criteria is a non-trivial task, and it falls short of being able to deliver complex filtering that is sometimes needed to simplify analysis.  Filtering of trace data was performed globally and applied to the trace affecting all of the events being collected.  Extended Events introduces a much better system of filtering using...(read more)

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  • When are predicates appropriate and what is the best pattern for usage

    - by Maxim Gershkovich
    When are predicates appropriate and what is the best pattern for usage? What are the advantages of predicates? It seems to me like most cases where a predicate can be employed a tight loop would accomplish the same functionality? I don’t see a reusability argument given you will probably only implement a predicate in one method right? They look and feel nice but besides that they seem like you would only employ them when you need a quick hack on the collection classes? UPDATE But why would you be rewriting the tight loop again and again? In my mind/code when it comes to collections I always end up with something like Class Person End Class Class PersonList Inherits List(Of Person) Function FindByName(Name) as Person tight loop.... End Function End Class @Ani By that same logic I could implement the method as such Class PersonList Inherits List(Of Person) Function FindByName(Name) as PersonList End Function Function FindByAge(Age) as PersonList End Function Function FindBySocialSecurityNumber(SocialSecurityNumber) as PersonList End Function End Class And call it as such Dim res as PersonList = MyList.FindByName("Max").FindByAge(25).FindBySocialSecurityNumber(1234) and the result along with the amount of code and its reusability is largely the same, no? I am not arguing just trying to understand.

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  • Haskell type signature with multiple type somethings (predicates?, for example Eq a =>)

    - by Andrew
    I'm not sure if type predicates is the right term, in fact I've never learned the word for this, so an edit to correct would be helpful - I'm referring to when you give the tipe of function f :: a -> b and you want to say a is a Eq and you say f :: Eq a => a -> b, the name for Eq a => - this is the thing i called a type predicate. My question, though, is how to have multiple of these, so if A is an Eq and B is a Num, I could say either f :: Eq a => a -> b or f :: Num b => a -> b. So, how can I have Eq a => and Num b => at the same time? f :: Eq a => Num b => a -> b, f :: Eq a -> Num b => a -> b, and f :: Eq a, Num b => a -> b all didn't do what I wanted.

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  • translating specifications into query predicates

    - by Jeroen
    I'm trying to find a nice and elegant way to query database content based on DDD "specifications". In domain driven design, a specification is used to check if some object, also known as the candidate, is compliant to a (domain specific) requirement. For example, the specification 'IsTaskDone' goes like: class IsTaskDone extends Specification<Task> { boolean isSatisfiedBy(Task candidate) { return candidate.isDone(); } } The above specification can be used for many purposes, e.g. it can be used to validate if a task has been completed, or to filter all completed tasks from a collection. However, I want to re-use this, nice, domain related specification to query on the database. Of course, the easiest solution would be to retrieve all entities of our desired type from the database, and filter that list in-memory by looping and removing non-matching entities. But clearly that would not be optimal for performance, especially when the entity count in our db increases. Proposal So my idea is to create a 'ConversionManager' that translates my specification into a persistence technique specific criteria, think of the JPA predicate class. The services looks as follows: public interface JpaSpecificationConversionManager { <T> Predicate getPredicateFor(Specification<T> specification, Root<T> root, CriteriaQuery<?> cq, CriteriaBuilder cb); JpaSpecificationConversionManager registerConverter(JpaSpecificationConverter<?, ?> converter); } By using our manager, the users can register their own conversion logic, isolating the domain related specification from persistence specific logic. To minimize the configuration of our manager, I want to use annotations on my converter classes, allowing the manager to automatically register those converters. JPA repository implementations could then use my manager, via dependency injection, to offer a find by specification method. Providing a find by specification should drastically reduce the number of methods on our repository interface. In theory, this all sounds decent, but I feel like I'm missing something critical. What do you guys think of my proposal, does it comply to the DDD way of thinking? Or is there already a framework that does something identical to what I just described?

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  • Howto use predicates in LINQ to Entities for Entity Framework objects

    - by user274947
    I'm using LINQ to Entities for Entity Framework objects in my Data Access Layer. My goal is to filter as much as I can from the database, without applying filtering logic on in-memory results. For that purpose Business Logic Layer passes a predicate to Data Access Layer. I mean Func<MyEntity, bool> So, if I use this predicate directly, like public IQueryable<MyEntity> GetAllMatchedEntities(Func<MyEntity, Boolean> isMatched) { return qry = _Context.MyEntities.Where(x => isMatched(x)); } I'm getting the exception [System.NotSupportedException] --- {"The LINQ expression node type 'Invoke' is not supported in LINQ to Entities."} Solution in that question suggests to use AsExpandable() method from LINQKit library. But again, using public IQueryable<MyEntity> GetAllMatchedEntities(Func<MyEntity, Boolean> isMatched) { return qry = _Context.MyEntities.AsExpandable().Where(x => isMatched(x)); } I'm getting the exception Unable to cast object of type 'System.Linq.Expressions.FieldExpression' to type 'System.Linq.Expressions.LambdaExpression' Is there way to use predicate in LINQ to Entities query for Entity Framework objects, so that it is correctly transformed it into a SQL statement. Thank you.

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  • Predicates and Lists

    - by George
    Hello guys, I have a generic list. Some elements of this list belong to a parent element. I retrieved all these elements from a database and i want to recursively build a tree with them. So, here's what i'm thinking: Here is my predicate: public static bool FindChildren(Int32 parentId,CategoryMapping catMapping) { if (catMapping.parentId == parentId) { return true; } else { return false; } } root = list[0]; root.childrenElements = root.FindAll(FindChildren(root.id,???) I can't figure out how this would work. How can i do this kind of predicate?

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  • Core Data Predicates with Subclassed NSManagedObjects

    - by coneybeare
    I have an AUDIO class. This audio has a SOUND_A subclass and a SOUND_B subclass. This is all done correctly and is working fine. I have another model, lets call it PLAYLIST_JOIN, and this can contain (in the real world) SOUND_A's and SOUND_B's, so we give it a relationship of AUDIO and PLAYLIST. This all works in the app. The problem I am having now is querying the PLAYLIST_JOIN table with an NSPredicate. What I want to do is find an exact PLAYLIST_JOIN item by giving it 2 keys in the predicate sound_a._sound_a_id = %@ && playlist.playlist_id = %@ and sound_b.sound_b_id = %@ && playlist.playlist_id = %@ The main problem is that because the table does not store sound_a and sound_b, but stored audio, I cannot use this syntax. I do not have the option of reorganizing the sound_a and sound_b to use the same _id attribute name, so how do I do this? Can I pass a method to the predicate? something like this: [audio getID] = %@ && playlist_id = %@

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  • mismatchedtoken with antlr syntactic predicates

    - by varzan
    I have the following lexer rules in my grammar file: LINE : 'F' | 'G'; RULE : (('->' ('F' | 'G')) => 'F' | 'G' ) | LINE LINE + | LINE * (ROTATE + LINE+)+ ; fragment ROTATE : ('/' | '\\'); I'm basically trying to match productions that look like F - F/F\F\F/F. It successfully matches stuff like the above, but I'm guessing there's a problem with my syntactic predicate, since G - G produces a MismatchedTokenException. The predicate serves to disambiguate between single letters on the lhs of '-', which I want to be recognized as the LINE token, and those on the rhs, which should be RULEs. Any idea what I'm doing wrong?

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  • So does Apple recommend to not use predicates and sort descriptors in an NSFetchRequest?

    - by dontWatchMyProfile
    From the docs: To summarize, though, if you execute a fetch directly, you should typically not add Objective-C-based predicates or sort descriptors to the fetch request. Instead you should apply these to the results of the fetch. If you use an array controller, you may need to subclass NSArrayController so you can have it not pass the sort descriptors to the persistent store and instead do the sorting after your data has been fetched. I don't get it. What's wrong with using them on fetch requests? Isn't it stupid to get back a whole big bunch of managed objects just to pick out a 1% of them in memory, leaving 99% garbage floating around? Isn't it much better to only fetch from the persistent store what you really need, in the order you need it? Probably I did get that wrong...

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  • Try a sample: Using the counter predicate for event sampling

    - by extended_events
    Extended Events offers a rich filtering mechanism, called predicates, that allows you to reduce the number of events you collect by specifying criteria that will be applied during event collection. (You can find more information about predicates in Using SQL Server 2008 Extended Events (by Jonathan Kehayias)) By evaluating predicates early in the event firing sequence we can reduce the performance impact of collecting events by stopping event collection when the criteria are not met. You can specify predicates on both event fields and on a special object called a predicate source. Predicate sources are similar to action in that they typically are related to some type of global information available from the server. You will find that many of the actions available in Extended Events have equivalent predicate sources, but actions and predicates sources are not the same thing. Applying predicates, whether on a field or predicate source, is very similar to what you are used to in T-SQL in terms of how they work; you pick some field/source and compare it to a value, for example, session_id = 52. There is one predicate source that merits special attention though, not just for its special use, but for how the order of predicate evaluation impacts the behavior you see. I’m referring to the counter predicate source. The counter predicate source gives you a way to sample a subset of events that otherwise meet the criteria of the predicate; for example you could collect every other event, or only every tenth event. Simple CountingThe counter predicate source works by creating an in memory counter that increments every time the predicate statement is evaluated. Here is a simple example with my favorite event, sql_statement_completed, that only collects the second statement that is run. (OK, that’s not much of a sample, but this is for demonstration purposes. Here is the session definition: CREATE EVENT SESSION counter_test ON SERVERADD EVENT sqlserver.sql_statement_completed    (ACTION (sqlserver.sql_text)    WHERE package0.counter = 2)ADD TARGET package0.ring_bufferWITH (MAX_DISPATCH_LATENCY = 1 SECONDS) You can find general information about the session DDL syntax in BOL and from Pedro’s post Introduction to Extended Events. The important part here is the WHERE statement that defines that I only what the event where package0.count = 2; in other words, only the second instance of the event. Notice that I need to provide the package name along with the predicate source. You don’t need to provide the package name if you’re using event fields, only for predicate sources. Let’s say I run the following test queries: -- Run three statements to test the sessionSELECT 'This is the first statement'GOSELECT 'This is the second statement'GOSELECT 'This is the third statement';GO Once you return the event data from the ring buffer and parse the XML (see my earlier post on reading event data) you should see something like this: event_name sql_text sql_statement_completed SELECT ‘This is the second statement’ You can see that only the second statement from the test was actually collected. (Feel free to try this yourself. Check out what happens if you remove the WHERE statement from your session. Go ahead, I’ll wait.) Percentage Sampling OK, so that wasn’t particularly interesting, but you can probably see that this could be interesting, for example, lets say I need a 25% sample of the statements executed on my server for some type of QA analysis, that might be more interesting than just the second statement. All comparisons of predicates are handled using an object called a predicate comparator; the simple comparisons such as equals, greater than, etc. are mapped to the common mathematical symbols you know and love (eg. = and >), but to do the less common comparisons you will need to use the predicate comparators directly. You would probably look to the MOD operation to do this type sampling; we would too, but we don’t call it MOD, we call it divides_by_uint64. This comparator evaluates whether one number is divisible by another with no remainder. The general syntax for using a predicate comparator is pred_comp(field, value), field is always first and value is always second. So lets take a look at how the session changes to answer our new question of 25% sampling: CREATE EVENT SESSION counter_test_25 ON SERVERADD EVENT sqlserver.sql_statement_completed    (ACTION (sqlserver.sql_text)    WHERE package0.divides_by_uint64(package0.counter,4))ADD TARGET package0.ring_bufferWITH (MAX_DISPATCH_LATENCY = 1 SECONDS)GO Here I’ve replaced the simple equivalency check with the divides_by_uint64 comparator to check if the counter is evenly divisible by 4, which gives us back every fourth record. I’ll leave it as an exercise for the reader to test this session. Why order matters I indicated at the start of this post that order matters when it comes to the counter predicate – it does. Like most other predicate systems, Extended Events evaluates the predicate statement from left to right; as soon as the predicate statement is proven false we abandon evaluation of the remainder of the statement. The counter predicate source is only incremented when it is evaluated so whether or not the counter is incremented will depend on where it is in the predicate statement and whether a previous criteria made the predicate false or not. Here is a generic example: Pred1: (WHERE statement_1 AND package0.counter = 2)Pred2: (WHERE package0.counter = 2 AND statement_1) Let’s say I cause a number of events as follows and examine what happens to the counter predicate source. Iteration Statement Pred1 Counter Pred2 Counter A Not statement_1 0 1 B statement_1 1 2 C Not statement_1 1 3 D statement_1 2 4 As you can see, in the case of Pred1, statement_1 is evaluated first, when it fails (A & C) predicate evaluation is stopped and the counter is not incremented. With Pred2 the counter is evaluated first, so it is incremented on every iteration of the event and the remaining parts of the predicate are then evaluated. In this example, Pred1 would return an event for D while Pred2 would return an event for B. But wait, there is an interesting side-effect here; consider Pred2 if I had run my statements in the following order: Not statement_1 Not statement_1 statement_1 statement_1 In this case I would never get an event back from the system because the point at which counter=2, the rest of the predicate evaluates as false so the event is not returned. If you’re using the counter target for sampling and you’re not getting the expected events, or any events, check the order of the predicate criteria. As a general rule I’d suggest that the counter criteria should be the last element of your predicate statement since that will assure that your sampling rate will apply to the set of event records defined by the rest of your predicate. Aside: I’m interested in hearing about uses for putting the counter predicate criteria earlier in the predicate statement. If you have one, post it in a comment to share with the class. - Mike Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • Selecting an element based on class and id in jquery - similar to an SQL query

    - by Ankur
    I want to select an element based on it's class and id, I have seen many similar questions on SO. Most of the users ask why would you ever want to do this - which is not very helpful, trust me, this is the simplest way of solving my UI problem, and it's a very unique and intereting UI related to making generic triple stores easily browsable. At the moment the jQUery looks like this: $(document).ready( function() { $(".predicates").hide(); $(".objects").hide(); $("#subject").click( function() { $("#predId, .predicates").toggle(); // this line } ); $("#predId").click( function() { $("#objId, .objects").toggle(); } ); }); The line I am really interested in is this $("#predId, .predicates").toggle(); how do I get the select to ensure that both #predId and .predicates are true, at the moment it seems that only one or the other has to be true. Is there something like an && operator?

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  • Looking for terminology for the relation of a subject and a predicate

    - by kostja
    While writing some predicates for collection filtering I have stumbled over the choice of the right words for the relation of the subject and the predicate (English is a foreign language for me). What I ended up writing was "Subjects matching this predicate..." This seems to be incorrect, since predicates are functions and not regular expressions. But saying "Subjects for which this predicate returns true..." sounds awkward to me as well.. So what would be the correct term?

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  • Introduction to Extended Events

    - by extended_events
    For those fighting with all the Extended Event terminology, let's step back and have a small overall Introduction to Extended Events. This post will give you a simplified end to end view through some of the elements in Extended Events. Before we start, let’s review the first Extented Events that we are going to use: -          Events: The SQL Server code is populated with event calls that, by default, are disabled. Adding events to a session enables those event calls. Once enabled, they will execute the set of functionality defined by the session. -          Target: This is an Extended Event Object that can be used to log event information. Also it is important to understand the following Extended Event concept: -          Session: Server Object created by the user that defines functionality to be executed every time a set of events happen.   It’s time to write a small “Hello World” using Extended Events. This will help understand the above terms. We will use: -          Event sqlserver. error_reported: This event gets fired every time that an error happens in the server. -          Target package0.asynchronous_file_target: This target stores the event data in disk. -          Session: We will create a session that sends all the error_reported events to the ring buffer. Before we get started, a quick note: Don’t run this script in a production environment. Even though, we are going just going to be raise very low severity user errors, we don't want to introduce noise in our servers. -- TRIES TO ELIMINATE PREVIOUS SESSIONS BEGIN TRY       DROP EVENT SESSION test_session ON SERVER END TRY BEGIN CATCH END CATCH GO   -- CREATES THE SESSION CREATE EVENT SESSION test_session ON SERVER ADD EVENT sqlserver.error_reported ADD TARGET package0.asynchronous_file_target -- CONFIGURES THE FILE TARGET (set filename = 'c:\temp\data1.xel' , metadatafile = 'c:\temp\data1.xem') GO   -- STARTS THE SESSION ALTER EVENT SESSION test_session ON SERVER STATE = START GO   -- GENERATES AN ERROR RAISERROR (N'HELLO WORLD', -- Message text.            1, -- Severity,            1, 7, 3, N'abcde'); -- Other parameters GO   -- STOPS LISTENING FOR THE EVENT ALTER EVENT SESSION test_session ON SERVER STATE = STOP GO   -- REMOVES THE EVENT SESSION FROM THE SERVER DROP EVENT SESSION test_session ON SERVER GO -- REMOVES THE EVENT SESSION FROM THE SERVER select CAST(event_data as XML) as event_data from sys.fn_xe_file_target_read_file ('c:\temp\data1*.xel','c:\temp\data1*.xem', null, null) This query will output the event data with our first hello world in the Extended Event format: <event name="error_reported" package="sqlserver" id="100" version="1" timestamp="2010-02-27T03:08:04.210Z"><data name="error"><value>50000</value><text /></data><data name="severity"><value>1</value><text /></data><data name="state"><value>1</value><text /></data><data name="user_defined"><value>true</value><text /></data><data name="message"><value>HELLO WORLD</value><text /></data></event> More on parsing event data in this post: Reading event data 101 Now let's move that lets move on to the other three Extended Event objects: -          Actions. This Extended Objects actions get executed before events are published (stored in buffers to be transferred to the targets). Currently they are used additional data (like the TSQL Statement related to an event, the session, the user) or generate a mini dump.   -          Predicates: Predicates express are logical expressions that specify what predicates to fire (E.g. only listen to errors with a severity greater than 16). This are composed of two Extended Objects: o   Predicate comparators: Defines an operator for a pair of values. Examples: §  Severity > 16 §  error_message = ‘Hello World!!’ o   Predicate sources: These are values that can be also used by the predicates. They are generic data that isn’t usually provided in the event (similar to the actions). §  Sqlserver.username = ‘Tintin’ As logical expressions they can be combined using logical operators (and, or, not).  Note: This pair always has to be first an event field or predicate source and then a value         Let’s do another small Example. We will trigger errors but we will use the ones that have severity >= 10 and the error message != ‘filter’. To verify this we will use the action sql_text that will attach the sql statement to the event data: -- TRIES TO ELIMINATE PREVIOUS SESSIONS BEGIN TRY       DROP EVENT SESSION test_session ON SERVER END TRY BEGIN CATCH END CATCH GO   -- CREATES THE SESSION CREATE EVENT SESSION test_session ON SERVER ADD EVENT sqlserver.error_reported       (ACTION (sqlserver.sql_text) WHERE severity = 2 and (not (message = 'filter'))) ADD TARGET package0.asynchronous_file_target -- CONFIGURES THE FILE TARGET (set filename = 'c:\temp\data2.xel' , metadatafile = 'c:\temp\data2.xem') GO   -- STARTS THE SESSION ALTER EVENT SESSION test_session ON SERVER STATE = START GO   -- THIS EVENT WILL BE FILTERED BECAUSE SEVERITY != 2 RAISERROR (N'PUBLISH', 1, 1, 7, 3, N'abcde'); GO -- THIS EVENT WILL BE FILTERED BECAUSE MESSAGE = 'FILTER' RAISERROR (N'FILTER', 2, 1, 7, 3, N'abcde'); GO -- THIS ERROR WILL BE PUBLISHED RAISERROR (N'PUBLISH', 2, 1, 7, 3, N'abcde'); GO   -- STOPS LISTENING FOR THE EVENT ALTER EVENT SESSION test_session ON SERVER STATE = STOP GO   -- REMOVES THE EVENT SESSION FROM THE SERVER DROP EVENT SESSION test_session ON SERVER GO -- REMOVES THE EVENT SESSION FROM THE SERVER select CAST(event_data as XML) as event_data from sys.fn_xe_file_target_read_file ('c:\temp\data2*.xel','c:\temp\data2*.xem', null, null)   This last statement will output one event with the following data: <event name="error_reported" package="sqlserver" id="100" version="1" timestamp="2010-03-05T23:15:05.481Z">   <data name="error">     <value>50000</value>     <text />   </data>   <data name="severity">     <value>2</value>     <text />   </data>   <data name="state">     <value>1</value>     <text />   </data>   <data name="user_defined">     <value>true</value>     <text />   </data>   <data name="message">     <value>PUBLISH</value>     <text />   </data>   <action name="sql_text" package="sqlserver">     <value>-- THIS ERROR WILL BE PUBLISHED RAISERROR (N'PUBLISH', 2, 1, 7, 3, N'abcde'); </value>     <text />   </action> </event> If you see more events, check if you have deleted previous event files. If so, please run   -- Deletes previous event files EXEC SP_CONFIGURE GO EXEC SP_CONFIGURE 'xp_cmdshell', 1 GO RECONFIGURE GO XP_CMDSHELL 'del c:\temp\data*.xe*' GO   or delete them manually.   More Info on Events: Extended Event Events More Info on Targets: Extended Event Targets More Info on Sessions: Extended Event Sessions More Info on Actions: Extended Event Actions More Info on Predicates: Extended Event Predicates Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • C#/.NET Little Wonders: The Generic Func Delegates

    - by James Michael Hare
    Once again, in this series of posts I look at the parts of the .NET Framework that may seem trivial, but can help improve your code by making it easier to write and maintain. The index of all my past little wonders posts can be found here. Back in one of my three original “Little Wonders” Trilogy of posts, I had listed generic delegates as one of the Little Wonders of .NET.  Later, someone posted a comment saying said that they would love more detail on the generic delegates and their uses, since my original entry just scratched the surface of them. Last week, I began our look at some of the handy generic delegates built into .NET with a description of delegates in general, and the Action family of delegates.  For this week, I’ll launch into a look at the Func family of generic delegates and how they can be used to support generic, reusable algorithms and classes. Quick Delegate Recap Delegates are similar to function pointers in C++ in that they allow you to store a reference to a method.  They can store references to either static or instance methods, and can actually be used to chain several methods together in one delegate. Delegates are very type-safe and can be satisfied with any standard method, anonymous method, or a lambda expression.  They can also be null as well (refers to no method), so care should be taken to make sure that the delegate is not null before you invoke it. Delegates are defined using the keyword delegate, where the delegate’s type name is placed where you would typically place the method name: 1: // This delegate matches any method that takes string, returns nothing 2: public delegate void Log(string message); This delegate defines a delegate type named Log that can be used to store references to any method(s) that satisfies its signature (whether instance, static, lambda expression, etc.). Delegate instances then can be assigned zero (null) or more methods using the operator = which replaces the existing delegate chain, or by using the operator += which adds a method to the end of a delegate chain: 1: // creates a delegate instance named currentLogger defaulted to Console.WriteLine (static method) 2: Log currentLogger = Console.Out.WriteLine; 3:  4: // invokes the delegate, which writes to the console out 5: currentLogger("Hi Standard Out!"); 6:  7: // append a delegate to Console.Error.WriteLine to go to std error 8: currentLogger += Console.Error.WriteLine; 9:  10: // invokes the delegate chain and writes message to std out and std err 11: currentLogger("Hi Standard Out and Error!"); While delegates give us a lot of power, it can be cumbersome to re-create fairly standard delegate definitions repeatedly, for this purpose the generic delegates were introduced in various stages in .NET.  These support various method types with particular signatures. Note: a caveat with generic delegates is that while they can support multiple parameters, they do not match methods that contains ref or out parameters. If you want to a delegate to represent methods that takes ref or out parameters, you will need to create a custom delegate. We’ve got the Func… delegates Just like it’s cousin, the Action delegate family, the Func delegate family gives us a lot of power to use generic delegates to make classes and algorithms more generic.  Using them keeps us from having to define a new delegate type when need to make a class or algorithm generic. Remember that the point of the Action delegate family was to be able to perform an “action” on an item, with no return results.  Thus Action delegates can be used to represent most methods that take 0 to 16 arguments but return void.  You can assign a method The Func delegate family was introduced in .NET 3.5 with the advent of LINQ, and gives us the power to define a function that can be called on 0 to 16 arguments and returns a result.  Thus, the main difference between Action and Func, from a delegate perspective, is that Actions return nothing, but Funcs return a result. The Func family of delegates have signatures as follows: Func<TResult> – matches a method that takes no arguments, and returns value of type TResult. Func<T, TResult> – matches a method that takes an argument of type T, and returns value of type TResult. Func<T1, T2, TResult> – matches a method that takes arguments of type T1 and T2, and returns value of type TResult. Func<T1, T2, …, TResult> – and so on up to 16 arguments, and returns value of type TResult. These are handy because they quickly allow you to be able to specify that a method or class you design will perform a function to produce a result as long as the method you specify meets the signature. For example, let’s say you were designing a generic aggregator, and you wanted to allow the user to define how the values will be aggregated into the result (i.e. Sum, Min, Max, etc…).  To do this, we would ask the user of our class to pass in a method that would take the current total, the next value, and produce a new total.  A class like this could look like: 1: public sealed class Aggregator<TValue, TResult> 2: { 3: // holds method that takes previous result, combines with next value, creates new result 4: private Func<TResult, TValue, TResult> _aggregationMethod; 5:  6: // gets or sets the current result of aggregation 7: public TResult Result { get; private set; } 8:  9: // construct the aggregator given the method to use to aggregate values 10: public Aggregator(Func<TResult, TValue, TResult> aggregationMethod = null) 11: { 12: if (aggregationMethod == null) throw new ArgumentNullException("aggregationMethod"); 13:  14: _aggregationMethod = aggregationMethod; 15: } 16:  17: // method to add next value 18: public void Aggregate(TValue nextValue) 19: { 20: // performs the aggregation method function on the current result and next and sets to current result 21: Result = _aggregationMethod(Result, nextValue); 22: } 23: } Of course, LINQ already has an Aggregate extension method, but that works on a sequence of IEnumerable<T>, whereas this is designed to work more with aggregating single results over time (such as keeping track of a max response time for a service). We could then use this generic aggregator to find the sum of a series of values over time, or the max of a series of values over time (among other things): 1: // creates an aggregator that adds the next to the total to sum the values 2: var sumAggregator = new Aggregator<int, int>((total, next) => total + next); 3:  4: // creates an aggregator (using static method) that returns the max of previous result and next 5: var maxAggregator = new Aggregator<int, int>(Math.Max); So, if we were timing the response time of a web method every time it was called, we could pass that response time to both of these aggregators to get an idea of the total time spent in that web method, and the max time spent in any one call to the web method: 1: // total will be 13 and max 13 2: int responseTime = 13; 3: sumAggregator.Aggregate(responseTime); 4: maxAggregator.Aggregate(responseTime); 5:  6: // total will be 20 and max still 13 7: responseTime = 7; 8: sumAggregator.Aggregate(responseTime); 9: maxAggregator.Aggregate(responseTime); 10:  11: // total will be 40 and max now 20 12: responseTime = 20; 13: sumAggregator.Aggregate(responseTime); 14: maxAggregator.Aggregate(responseTime); The Func delegate family is useful for making generic algorithms and classes, and in particular allows the caller of the method or user of the class to specify a function to be performed in order to generate a result. What is the result of a Func delegate chain? If you remember, we said earlier that you can assign multiple methods to a delegate by using the += operator to chain them.  So how does this affect delegates such as Func that return a value, when applied to something like the code below? 1: Func<int, int, int> combo = null; 2:  3: // What if we wanted to aggregate the sum and max together? 4: combo += (total, next) => total + next; 5: combo += Math.Max; 6:  7: // what is the result? 8: var comboAggregator = new Aggregator<int, int>(combo); Well, in .NET if you chain multiple methods in a delegate, they will all get invoked, but the result of the delegate is the result of the last method invoked in the chain.  Thus, this aggregator would always result in the Math.Max() result.  The other chained method (the sum) gets executed first, but it’s result is thrown away: 1: // result is 13 2: int responseTime = 13; 3: comboAggregator.Aggregate(responseTime); 4:  5: // result is still 13 6: responseTime = 7; 7: comboAggregator.Aggregate(responseTime); 8:  9: // result is now 20 10: responseTime = 20; 11: comboAggregator.Aggregate(responseTime); So remember, you can chain multiple Func (or other delegates that return values) together, but if you do so you will only get the last executed result. Func delegates and co-variance/contra-variance in .NET 4.0 Just like the Action delegate, as of .NET 4.0, the Func delegate family is contra-variant on its arguments.  In addition, it is co-variant on its return type.  To support this, in .NET 4.0 the signatures of the Func delegates changed to: Func<out TResult> – matches a method that takes no arguments, and returns value of type TResult (or a more derived type). Func<in T, out TResult> – matches a method that takes an argument of type T (or a less derived type), and returns value of type TResult(or a more derived type). Func<in T1, in T2, out TResult> – matches a method that takes arguments of type T1 and T2 (or less derived types), and returns value of type TResult (or a more derived type). Func<in T1, in T2, …, out TResult> – and so on up to 16 arguments, and returns value of type TResult (or a more derived type). Notice the addition of the in and out keywords before each of the generic type placeholders.  As we saw last week, the in keyword is used to specify that a generic type can be contra-variant -- it can match the given type or a type that is less derived.  However, the out keyword, is used to specify that a generic type can be co-variant -- it can match the given type or a type that is more derived. On contra-variance, if you are saying you need an function that will accept a string, you can just as easily give it an function that accepts an object.  In other words, if you say “give me an function that will process dogs”, I could pass you a method that will process any animal, because all dogs are animals.  On the co-variance side, if you are saying you need a function that returns an object, you can just as easily pass it a function that returns a string because any string returned from the given method can be accepted by a delegate expecting an object result, since string is more derived.  Once again, in other words, if you say “give me a method that creates an animal”, I can pass you a method that will create a dog, because all dogs are animals. It really all makes sense, you can pass a more specific thing to a less specific parameter, and you can return a more specific thing as a less specific result.  In other words, pay attention to the direction the item travels (parameters go in, results come out).  Keeping that in mind, you can always pass more specific things in and return more specific things out. For example, in the code below, we have a method that takes a Func<object> to generate an object, but we can pass it a Func<string> because the return type of object can obviously accept a return value of string as well: 1: // since Func<object> is co-variant, this will access Func<string>, etc... 2: public static string Sequence(int count, Func<object> generator) 3: { 4: var builder = new StringBuilder(); 5:  6: for (int i=0; i<count; i++) 7: { 8: object value = generator(); 9: builder.Append(value); 10: } 11:  12: return builder.ToString(); 13: } Even though the method above takes a Func<object>, we can pass a Func<string> because the TResult type placeholder is co-variant and accepts types that are more derived as well: 1: // delegate that's typed to return string. 2: Func<string> stringGenerator = () => DateTime.Now.ToString(); 3:  4: // This will work in .NET 4.0, but not in previous versions 5: Sequence(100, stringGenerator); Previous versions of .NET implemented some forms of co-variance and contra-variance before, but .NET 4.0 goes one step further and allows you to pass or assign an Func<A, BResult> to a Func<Y, ZResult> as long as A is less derived (or same) as Y, and BResult is more derived (or same) as ZResult. Sidebar: The Func and the Predicate A method that takes one argument and returns a bool is generally thought of as a predicate.  Predicates are used to examine an item and determine whether that item satisfies a particular condition.  Predicates are typically unary, but you may also have binary and other predicates as well. Predicates are often used to filter results, such as in the LINQ Where() extension method: 1: var numbers = new[] { 1, 2, 4, 13, 8, 10, 27 }; 2:  3: // call Where() using a predicate which determines if the number is even 4: var evens = numbers.Where(num => num % 2 == 0); As of .NET 3.5, predicates are typically represented as Func<T, bool> where T is the type of the item to examine.  Previous to .NET 3.5, there was a Predicate<T> type that tended to be used (which we’ll discuss next week) and is still supported, but most developers recommend using Func<T, bool> now, as it prevents confusion with overloads that accept unary predicates and binary predicates, etc.: 1: // this seems more confusing as an overload set, because of Predicate vs Func 2: public static SomeMethod(Predicate<int> unaryPredicate) { } 3: public static SomeMethod(Func<int, int, bool> binaryPredicate) { } 4:  5: // this seems more consistent as an overload set, since just uses Func 6: public static SomeMethod(Func<int, bool> unaryPredicate) { } 7: public static SomeMethod(Func<int, int, bool> binaryPredicate) { } Also, even though Predicate<T> and Func<T, bool> match the same signatures, they are separate types!  Thus you cannot assign a Predicate<T> instance to a Func<T, bool> instance and vice versa: 1: // the same method, lambda expression, etc can be assigned to both 2: Predicate<int> isEven = i => (i % 2) == 0; 3: Func<int, bool> alsoIsEven = i => (i % 2) == 0; 4:  5: // but the delegate instances cannot be directly assigned, strongly typed! 6: // ERROR: cannot convert type... 7: isEven = alsoIsEven; 8:  9: // however, you can assign by wrapping in a new instance: 10: isEven = new Predicate<int>(alsoIsEven); 11: alsoIsEven = new Func<int, bool>(isEven); So, the general advice that seems to come from most developers is that Predicate<T> is still supported, but we should use Func<T, bool> for consistency in .NET 3.5 and above. Sidebar: Func as a Generator for Unit Testing One area of difficulty in unit testing can be unit testing code that is based on time of day.  We’d still want to unit test our code to make sure the logic is accurate, but we don’t want the results of our unit tests to be dependent on the time they are run. One way (of many) around this is to create an internal generator that will produce the “current” time of day.  This would default to returning result from DateTime.Now (or some other method), but we could inject specific times for our unit testing.  Generators are typically methods that return (generate) a value for use in a class/method. For example, say we are creating a CacheItem<T> class that represents an item in the cache, and we want to make sure the item shows as expired if the age is more than 30 seconds.  Such a class could look like: 1: // responsible for maintaining an item of type T in the cache 2: public sealed class CacheItem<T> 3: { 4: // helper method that returns the current time 5: private static Func<DateTime> _timeGenerator = () => DateTime.Now; 6:  7: // allows internal access to the time generator 8: internal static Func<DateTime> TimeGenerator 9: { 10: get { return _timeGenerator; } 11: set { _timeGenerator = value; } 12: } 13:  14: // time the item was cached 15: public DateTime CachedTime { get; private set; } 16:  17: // the item cached 18: public T Value { get; private set; } 19:  20: // item is expired if older than 30 seconds 21: public bool IsExpired 22: { 23: get { return _timeGenerator() - CachedTime > TimeSpan.FromSeconds(30.0); } 24: } 25:  26: // creates the new cached item, setting cached time to "current" time 27: public CacheItem(T value) 28: { 29: Value = value; 30: CachedTime = _timeGenerator(); 31: } 32: } Then, we can use this construct to unit test our CacheItem<T> without any time dependencies: 1: var baseTime = DateTime.Now; 2:  3: // start with current time stored above (so doesn't drift) 4: CacheItem<int>.TimeGenerator = () => baseTime; 5:  6: var target = new CacheItem<int>(13); 7:  8: // now add 15 seconds, should still be non-expired 9: CacheItem<int>.TimeGenerator = () => baseTime.AddSeconds(15); 10:  11: Assert.IsFalse(target.IsExpired); 12:  13: // now add 31 seconds, should now be expired 14: CacheItem<int>.TimeGenerator = () => baseTime.AddSeconds(31); 15:  16: Assert.IsTrue(target.IsExpired); Now we can unit test for 1 second before, 1 second after, 1 millisecond before, 1 day after, etc.  Func delegates can be a handy tool for this type of value generation to support more testable code.  Summary Generic delegates give us a lot of power to make truly generic algorithms and classes.  The Func family of delegates is a great way to be able to specify functions to calculate a result based on 0-16 arguments.  Stay tuned in the weeks that follow for other generic delegates in the .NET Framework!   Tweet Technorati Tags: .NET, C#, CSharp, Little Wonders, Generics, Func, Delegates

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  • Linq PredicateBuilder with conditional AND, OR and NOT filters.

    - by richeym
    We have a project using LINQ to SQL, for which I need to rewrite a couple of search pages to allow the client to select whether they wish to perform an and or an or search. I though about redoing the LINQ queries using PredicateBuilder and have got this working pretty well I think. I effectively have a class containing my predicates, e.g.: internal static Expression<Func<Job, bool>> Description(string term) { return p => p.Description.Contains(term); } To perform the search i'm doing this (some code omitted for brevity): public Expression<Func<Job, bool>> ToLinqExpression() { var predicates = new List<Expression<Func<Job, bool>>>(); // build up predicates here if (SearchType == SearchType.And) { query = PredicateBuilder.True<Job>(); } else { query = PredicateBuilder.False<Job>(); } foreach (var predicate in predicates) { if (SearchType == SearchType.And) { query = query.And(predicate); } else { query = query.Or(predicate); } } return query; } While i'm reasonably happy with this, I have two concerns: The if/else blocks that evaluate a SearchType property feel like they could be a potential code smell. The client is now insisting on being able to perform 'and not' / 'or not' searches. To address point 2, I think I could do this by simply rewriting my expressions, e.g.: internal static Expression<Func<Job, bool>> Description(string term, bool invert) { if (invert) { return p => !p.Description.Contains(term); } else { return p => p.Description.Contains(term); } } However this feels like a bit of a kludge, which usually means there's a better solution out there. Can anyone recommend how this could be improved? I'm aware of dynamic LINQ, but I don't really want to lose LINQ's strong typing.

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  • Basics of Join Predicate Pushdown in Oracle

    - by Maria Colgan
    Happy New Year to all of our readers! We hope you all had a great holiday season. We start the new year by continuing our series on Optimizer transformations. This time it is the turn of Predicate Pushdown. I would like to thank Rafi Ahmed for the content of this blog.Normally, a view cannot be joined with an index-based nested loop (i.e., index access) join, since a view, in contrast with a base table, does not have an index defined on it. A view can only be joined with other tables using three methods: hash, nested loop, and sort-merge joins. Introduction The join predicate pushdown (JPPD) transformation allows a view to be joined with index-based nested-loop join method, which may provide a more optimal alternative. In the join predicate pushdown transformation, the view remains a separate query block, but it contains the join predicate, which is pushed down from its containing query block into the view. The view thus becomes correlated and must be evaluated for each row of the outer query block. These pushed-down join predicates, once inside the view, open up new index access paths on the base tables inside the view; this allows the view to be joined with index-based nested-loop join method, thereby enabling the optimizer to select an efficient execution plan. The join predicate pushdown transformation is not always optimal. The join predicate pushed-down view becomes correlated and it must be evaluated for each outer row; if there is a large number of outer rows, the cost of evaluating the view multiple times may make the nested-loop join suboptimal, and therefore joining the view with hash or sort-merge join method may be more efficient. The decision whether to push down join predicates into a view is determined by evaluating the costs of the outer query with and without the join predicate pushdown transformation under Oracle's cost-based query transformation framework. The join predicate pushdown transformation applies to both non-mergeable views and mergeable views and to pre-defined and inline views as well as to views generated internally by the optimizer during various transformations. The following shows the types of views on which join predicate pushdown is currently supported. UNION ALL/UNION view Outer-joined view Anti-joined view Semi-joined view DISTINCT view GROUP-BY view Examples Consider query A, which has an outer-joined view V. The view cannot be merged, as it contains two tables, and the join between these two tables must be performed before the join between the view and the outer table T4. A: SELECT T4.unique1, V.unique3 FROM T_4K T4,            (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3) VWHERE T4.unique3 = V.hundred(+) AND       T4.ten = V.ten(+) AND       T4.thousand = 5; The following shows the non-default plan for query A generated by disabling join predicate pushdown. When query A undergoes join predicate pushdown, it yields query B. Note that query B is expressed in a non-standard SQL and shows an internal representation of the query. B: SELECT T4.unique1, V.unique3 FROM T_4K T4,           (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3             AND T4.unique3 = V.hundred(+)             AND T4.ten = V.ten(+)) V WHERE T4.thousand = 5; The execution plan for query B is shown below. In the execution plan BX, note the keyword 'VIEW PUSHED PREDICATE' indicates that the view has undergone the join predicate pushdown transformation. The join predicates (shown here in red) have been moved into the view V; these join predicates open up index access paths thereby enabling index-based nested-loop join of the view. With join predicate pushdown, the cost of query A has come down from 62 to 32.  As mentioned earlier, the join predicate pushdown transformation is cost-based, and a join predicate pushed-down plan is selected only when it reduces the overall cost. Consider another example of a query C, which contains a view with the UNION ALL set operator.C: SELECT R.unique1, V.unique3 FROM T_5K R,            (SELECT T1.unique3, T2.unique1+T1.unique1             FROM T_5K T1, T_10K T2             WHERE T1.unique1 = T2.unique1             UNION ALL             SELECT T1.unique3, T2.unique2             FROM G_4K T1, T_10K T2             WHERE T1.unique1 = T2.unique1) V WHERE R.unique3 = V.unique3 and R.thousand < 1; The execution plan of query C is shown below. In the above, 'VIEW UNION ALL PUSHED PREDICATE' indicates that the UNION ALL view has undergone the join predicate pushdown transformation. As can be seen, here the join predicate has been replicated and pushed inside every branch of the UNION ALL view. The join predicates (shown here in red) open up index access paths thereby enabling index-based nested loop join of the view. Consider query D as an example of join predicate pushdown into a distinct view. We have the following cardinalities of the tables involved in query D: Sales (1,016,271), Customers (50,000), and Costs (787,766).  D: SELECT C.cust_last_name, C.cust_city FROM customers C,            (SELECT DISTINCT S.cust_id             FROM sales S, costs CT             WHERE S.prod_id = CT.prod_id and CT.unit_price > 70) V WHERE C.cust_state_province = 'CA' and C.cust_id = V.cust_id; The execution plan of query D is shown below. As shown in XD, when query D undergoes join predicate pushdown transformation, the expensive DISTINCT operator is removed and the join is converted into a semi-join; this is possible, since all the SELECT list items of the view participate in an equi-join with the outer tables. Under similar conditions, when a group-by view undergoes join predicate pushdown transformation, the expensive group-by operator can also be removed. With the join predicate pushdown transformation, the elapsed time of query D came down from 63 seconds to 5 seconds. Since distinct and group-by views are mergeable views, the cost-based transformation framework also compares the cost of merging the view with that of join predicate pushdown in selecting the most optimal execution plan. Summary We have tried to illustrate the basic ideas behind join predicate pushdown on different types of views by showing example queries that are quite simple. Oracle can handle far more complex queries and other types of views not shown here in the examples. Again many thanks to Rafi Ahmed for the content of this blog post.

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  • How to use NSPredicate with Key-Paths (and ALL)?

    - by Konstantin
    Taking example from Apple docs using predicates with Key-Paths NSPredicate *predicate = [NSPredicate predicateWithFormat:@"ANY employees.firstName like 'Matthew'"]; Now, assume the employees has a bool field "isGood". The question: how do I select just those entities, having ALL of employees isGood==TRUE? I tried but failed with following predicates: "!(ANY employees.isGood != TRUE)" "(ALL employees.isGood == TRUE)" // Would be perfect, but throws an exception..

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  • How can I test for an empty Breeze predicate?

    - by Megan
    I'm using Breeze to filter data requested on the client. My code looks a little like this: Client - Creating Filter Predicate var predicates = []; var criteriaPredicate = null; $.each(selectedFilterCriteria(), function (index, item) { criteriaPredicate = (index == 0) ? breeze.Predicate.create('criteriaId', breeze.FilterQueryOp.Equals, item) : criteriaPredicate.or('criteriaId', breeze.FilterQueryOp.Equals, item); if (breeze.Predicate.isPredicate(criteriaPredicate)) { predicates.push(criteriaPredicate); } // Repeat for X Filter Criteria var filter = breeze.Predicate.and(predicates); return context.getAll(filter, data); Client - Context Query function getAll(predicate, dataObservable) { var query = breeze.EntityQuery.from('Data'); if (breeze.Predicate.isPredicate(predicate)) { query = query.where(predicate); } return manager.executeQuery(query).then(success).fail(failure); } Issue I'm having an issue with the request because, if there are no filters set, I apply an "empty" predicate (due to the var filter = breeze.Predicate.and([]) line) resulting in a request like http://mysite/api/app/Data?$filter=. The request is an invalid OData query since the value of the $filter argument cannot be empty. Is there a good way for me to check for an empty predicate? I know I can refactor my client code to not use a predicate unless there is at least one filterable item, but I thought I would check first to see if I overlooked some property or method on the Breeze Predicate.

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  • So…is it a Seek or a Scan?

    - by Paul White
    You’re probably most familiar with the terms ‘Seek’ and ‘Scan’ from the graphical plans produced by SQL Server Management Studio (SSMS).  The image to the left shows the most common ones, with the three types of scan at the top, followed by four types of seek.  You might look to the SSMS tool-tip descriptions to explain the differences between them: Not hugely helpful are they?  Both mention scans and ranges (nothing about seeks) and the Index Seek description implies that it will not scan the index entirely (which isn’t necessarily true). Recall also yesterday’s post where we saw two Clustered Index Seek operations doing very different things.  The first Seek performed 63 single-row seeking operations; and the second performed a ‘Range Scan’ (more on those later in this post).  I hope you agree that those were two very different operations, and perhaps you are wondering why there aren’t different graphical plan icons for Range Scans and Seeks?  I have often wondered about that, and the first person to mention it after yesterday’s post was Erin Stellato (twitter | blog): Before we go on to make sense of all this, let’s look at another example of how SQL Server confusingly mixes the terms ‘Scan’ and ‘Seek’ in different contexts.  The diagram below shows a very simple heap table with two columns, one of which is the non-clustered Primary Key, and the other has a non-unique non-clustered index defined on it.  The right hand side of the diagram shows a simple query, it’s associated query plan, and a couple of extracts from the SSMS tool-tip and Properties windows. Notice the ‘scan direction’ entry in the Properties window snippet.  Is this a seek or a scan?  The different references to Scans and Seeks are even more pronounced in the XML plan output that the graphical plan is based on.  This fragment is what lies behind the single Index Seek icon shown above: You’ll find the same confusing references to Seeks and Scans throughout the product and its documentation. Making Sense of Seeks Let’s forget all about scans for a moment, and think purely about seeks.  Loosely speaking, a seek is the process of navigating an index B-tree to find a particular index record, most often at the leaf level.  A seek starts at the root and navigates down through the levels of the index to find the point of interest: Singleton Lookups The simplest sort of seek predicate performs this traversal to find (at most) a single record.  This is the case when we search for a single value using a unique index and an equality predicate.  It should be readily apparent that this type of search will either find one record, or none at all.  This operation is known as a singleton lookup.  Given the example table from before, the following query is an example of a singleton lookup seek: Sadly, there’s nothing in the graphical plan or XML output to show that this is a singleton lookup – you have to infer it from the fact that this is a single-value equality seek on a unique index.  The other common examples of a singleton lookup are bookmark lookups – both the RID and Key Lookup forms are singleton lookups (an RID lookup finds a single record in a heap from the unique row locator, and a Key Lookup does much the same thing on a clustered table).  If you happen to run your query with STATISTICS IO ON, you will notice that ‘Scan Count’ is always zero for a singleton lookup. Range Scans The other type of seek predicate is a ‘seek plus range scan’, which I will refer to simply as a range scan.  The seek operation makes an initial descent into the index structure to find the first leaf row that qualifies, and then performs a range scan (either backwards or forwards in the index) until it reaches the end of the scan range. The ability of a range scan to proceed in either direction comes about because index pages at the same level are connected by a doubly-linked list – each page has a pointer to the previous page (in logical key order) as well as a pointer to the following page.  The doubly-linked list is represented by the green and red dotted arrows in the index diagram presented earlier.  One subtle (but important) point is that the notion of a ‘forward’ or ‘backward’ scan applies to the logical key order defined when the index was built.  In the present case, the non-clustered primary key index was created as follows: CREATE TABLE dbo.Example ( key_col INTEGER NOT NULL, data INTEGER NOT NULL, CONSTRAINT [PK dbo.Example key_col] PRIMARY KEY NONCLUSTERED (key_col ASC) ) ; Notice that the primary key index specifies an ascending sort order for the single key column.  This means that a forward scan of the index will retrieve keys in ascending order, while a backward scan would retrieve keys in descending key order.  If the index had been created instead on key_col DESC, a forward scan would retrieve keys in descending order, and a backward scan would return keys in ascending order. A range scan seek predicate may have a Start condition, an End condition, or both.  Where one is missing, the scan starts (or ends) at one extreme end of the index, depending on the scan direction.  Some examples might help clarify that: the following diagram shows four queries, each of which performs a single seek against a column holding every integer from 1 to 100 inclusive.  The results from each query are shown in the blue columns, and relevant attributes from the Properties window appear on the right: Query 1 specifies that all key_col values less than 5 should be returned in ascending order.  The query plan achieves this by seeking to the start of the index leaf (there is no explicit starting value) and scanning forward until the End condition (key_col < 5) is no longer satisfied (SQL Server knows it can stop looking as soon as it finds a key_col value that isn’t less than 5 because all later index entries are guaranteed to sort higher). Query 2 asks for key_col values greater than 95, in descending order.  SQL Server returns these results by seeking to the end of the index, and scanning backwards (in descending key order) until it comes across a row that isn’t greater than 95.  Sharp-eyed readers may notice that the end-of-scan condition is shown as a Start range value.  This is a bug in the XML show plan which bubbles up to the Properties window – when a backward scan is performed, the roles of the Start and End values are reversed, but the plan does not reflect that.  Oh well. Query 3 looks for key_col values that are greater than or equal to 10, and less than 15, in ascending order.  This time, SQL Server seeks to the first index record that matches the Start condition (key_col >= 10) and then scans forward through the leaf pages until the End condition (key_col < 15) is no longer met. Query 4 performs much the same sort of operation as Query 3, but requests the output in descending order.  Again, we have to mentally reverse the Start and End conditions because of the bug, but otherwise the process is the same as always: SQL Server finds the highest-sorting record that meets the condition ‘key_col < 25’ and scans backward until ‘key_col >= 20’ is no longer true. One final point to note: seek operations always have the Ordered: True attribute.  This means that the operator always produces rows in a sorted order, either ascending or descending depending on how the index was defined, and whether the scan part of the operation is forward or backward.  You cannot rely on this sort order in your queries of course (you must always specify an ORDER BY clause if order is important) but SQL Server can make use of the sort order internally.  In the four queries above, the query optimizer was able to avoid an explicit Sort operator to honour the ORDER BY clause, for example. Multiple Seek Predicates As we saw yesterday, a single index seek plan operator can contain one or more seek predicates.  These seek predicates can either be all singleton seeks or all range scans – SQL Server does not mix them.  For example, you might expect the following query to contain two seek predicates, a singleton seek to find the single record in the unique index where key_col = 10, and a range scan to find the key_col values between 15 and 20: SELECT key_col FROM dbo.Example WHERE key_col = 10 OR key_col BETWEEN 15 AND 20 ORDER BY key_col ASC ; In fact, SQL Server transforms the singleton seek (key_col = 10) to the equivalent range scan, Start:[key_col >= 10], End:[key_col <= 10].  This allows both range scans to be evaluated by a single seek operator.  To be clear, this query results in two range scans: one from 10 to 10, and one from 15 to 20. Final Thoughts That’s it for today – tomorrow we’ll look at monitoring singleton lookups and range scans, and I’ll show you a seek on a heap table. Yes, a seek.  On a heap.  Not an index! If you would like to run the queries in this post for yourself, there’s a script below.  Thanks for reading! IF OBJECT_ID(N'dbo.Example', N'U') IS NOT NULL BEGIN DROP TABLE dbo.Example; END ; -- Test table is a heap -- Non-clustered primary key on 'key_col' CREATE TABLE dbo.Example ( key_col INTEGER NOT NULL, data INTEGER NOT NULL, CONSTRAINT [PK dbo.Example key_col] PRIMARY KEY NONCLUSTERED (key_col) ) ; -- Non-unique non-clustered index on the 'data' column CREATE NONCLUSTERED INDEX [IX dbo.Example data] ON dbo.Example (data) ; -- Add 100 rows INSERT dbo.Example WITH (TABLOCKX) ( key_col, data ) SELECT key_col = V.number, data = V.number FROM master.dbo.spt_values AS V WHERE V.[type] = N'P' AND V.number BETWEEN 1 AND 100 ; -- ================ -- Singleton lookup -- ================ ; -- Single value equality seek in a unique index -- Scan count = 0 when STATISTIS IO is ON -- Check the XML SHOWPLAN SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col = 32 ; -- =========== -- Range Scans -- =========== ; -- Query 1 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col <= 5 ORDER BY E.key_col ASC ; -- Query 2 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col > 95 ORDER BY E.key_col DESC ; -- Query 3 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col >= 10 AND E.key_col < 15 ORDER BY E.key_col ASC ; -- Query 4 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col >= 20 AND E.key_col < 25 ORDER BY E.key_col DESC ; -- Final query (singleton + range = 2 range scans) SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col = 10 OR E.key_col BETWEEN 15 AND 20 ORDER BY E.key_col ASC ; -- === TIDY UP === DROP TABLE dbo.Example; © 2011 Paul White email: [email protected] twitter: @SQL_Kiwi

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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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  • Core Data NSPredicate for relationships.

    - by Mugunth Kumar
    My object graph is simple. I've a feedentry object that stores info about RSS feeds and a relationship called Tag that links to "TagValues" object. Both the relation (to and inverse) are to-many. i.e, a feed can have multiple tags and a tag can be associated to multiple feeds. I referred to http://stackoverflow.com/questions/844162/how-to-do-core-data-queries-through-a-relationship and created a NSFetchRequest. But when fetch data, I get an exception stating, NSInvalidArgumentException unimplemented SQL generation for predicate What should I do? I'm a newbie to core data :( I know I've done something terribly wrong... Please help... Thanks -- NSFetchRequest *fetchRequest = [[NSFetchRequest alloc] init]; // Edit the entity name as appropriate. NSEntityDescription *entity = [NSEntityDescription entityForName:@"FeedEntry" inManagedObjectContext:managedObjectContext]; [fetchRequest setEntity:entity]; // Edit the sort key as appropriate. NSSortDescriptor *sortDescriptor = [[NSSortDescriptor alloc] initWithKey:@"authorname" ascending:NO]; NSArray *sortDescriptors = [[NSArray alloc] initWithObjects:sortDescriptor, nil]; [fetchRequest setSortDescriptors:sortDescriptors]; NSEntityDescription *tagEntity = [NSEntityDescription entityForName:@"TagValues" inManagedObjectContext:self.managedObjectContext]; NSPredicate *tagPredicate = [NSPredicate predicateWithFormat:@"tagName LIKE[c] 'nyt'"]; NSFetchRequest *tagRequest = [[NSFetchRequest alloc] init]; [tagRequest setEntity:tagEntity]; [tagRequest setPredicate:tagPredicate]; NSError *error = nil; NSArray* predicates = [self.managedObjectContext executeFetchRequest:tagRequest error:&error]; TagValues *tv = (TagValues*) [predicates objectAtIndex:0]; NSLog(tv.tagName); // it is nyt here... NSPredicate *predicate = [NSPredicate predicateWithFormat:@"tag IN %@", predicates]; [fetchRequest setPredicate:predicate]; // Edit the section name key path and cache name if appropriate. // nil for section name key path means "no sections". NSFetchedResultsController *aFetchedResultsController = [[NSFetchedResultsController alloc] initWithFetchRequest:fetchRequest managedObjectContext:managedObjectContext sectionNameKeyPath:nil cacheName:@"Root"]; aFetchedResultsController.delegate = self; self.fetchedResultsController = aFetchedResultsController; --

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  • Is eval the defmacro of javascript?

    - by Florian Margaine
    In Common Lisp, defmacro basically allows us to build our own DSL. I read this page today and it explains something cleverly done: But I wasn't about to write out all these boring predicates myself, so I defined a function that, given a list of words, builds up the text for such a predicate automatically, and then evals it to produce a function. Which just looks like defmacro to me. Is eval the defmacro of javascript? Could it be used as such?

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