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• $query returns results but not the ones i want: $query looks good to me :S

  - by Toni Michel Caubet

  I'll start again, Lets say My data is: Table element (id,name,....) 1, name element 1, .... 2, name element 2, .... 3, name element 3, .... Table tags (id,name,id_element, ....) 1, happy , 1 2, result, 1 3, very , 1 4, element, 2 5, another, 3 6, element, 1 7, happy, 2 So if search is 'very, happy,element,result': Results i would like 1) element with id = 2 because it has all tags 2) element with id = 1 because it has the tag 'element' and the tag 'happy' (only 2 less taggs) 3) .... (only 3 less taggs) So if search is 'happy,element': Results i would like 1) element with id = 1 because it has all tags (and no more) 2) element with id = 2 because it has the tag 'element' and the tag 'happy' (and two more tags) 3) .... and 3 more tags This is an echo to my query: (it doesn't fit al requirements i wrote, but its first test to find with matched tags) SELECT element.id as id_deseada,tagg.* FROM element,tagg WHERE tagg.id_element = element.id AND tagg.nombre IN ('happy','tagg','result') GROUP BY tagg.id_element ORDER BY element.votos This returns 10 duplicated elements... :S and doen't even have all taggs (and on database there are taggs with 'happy' results) if it helps, thats how i get the elements of a tag (by name and with only one tagg) $query = "SELECT element.id FROM element,tagg WHERE tagg.nombre = '$nombre_tagg' AND tagg.id_element = element.id AND lan = '$lan' GROUP BY tagg.id_element"; I hope it's a bit easier to understand now, excuse my english.. :) Thanks a lot for you possible aportation!

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• Mongodb vs. Cassandra

  - by ming yeow

  I am evaluating what might be the best migration option. Currently, i am on a sharded mysql (horizontal partition), with most of my data stored in json blobs. I do not have any complex SQL queries( already migrated away after since I partitioned my db) Right now, it seems like both Mongodb and Cassandra would be likely options. My situation lots of reads in every query, less regular writes not worried about "massive" scalability more concerned about simple setup, maintenance and code minimize hardware/server cost

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• MongoDB transactions?

  - by Arnis L.

  Playing around with MongoDB and NoRM in .NET. Thing that confused me - there are no transactions (can't just tell MongoConnection.Begin/EndTransaction or something like that). I want to use Unit of work pattern and rollback changes in case something fails. Is there still a clean way how to enrich my repository with ITransaction?

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• Mongodb Query To select records having a given key

  - by sagar

  let the records in database are {"_id":"1","fn":"sagar","ln":"Varpe"} {"_id":"1","fn":"sag","score":"10"} {"_id":"1","ln":"ln1","score":"10"} {"_id":"1","ln":"ln2"} I need to design a MongoDB query to find all records who has a given key like if i pass "ln" as a parameter to query it shold return all records in which "ln"is a Key , the results fo are {"_id":"1","fn":"sagar","ln":"Varpe"} {"_id":"1","ln":"ln1","score":"10"} {"_id":"1","ln":"ln2"}

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• MongoDB index/RAM relationship

  - by Tegan Clark

  I'm about to adopt MongoDB for a new project and I've chosen it for flexibility, not scalability. From the documentation and web posts I keep reading that all indexes are in RAM. This just isn't making sense to me as my indexes will easily be larger than the amount of available RAM. Can anyone share some insight on the index/RAM relationship and what happens when both an individual index and all of my indexes exceed the size of available RAM?

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• Calculated group-by fields in MongoDB

  - by Navin Viswanath

  For this example from the MongoDB documentation, how do I write the query using MongoTemplate? db.sales.aggregate( [ { $group : { _id : { month: { $month: "$date" }, day: { $dayOfMonth: "$date" }, year: { $year: "$date" } }, totalPrice: { $sum: { $multiply: [ "$price", "$quantity" ] } }, averageQuantity: { $avg: "$quantity" }, count: { $sum: 1 } } } ] ) Or in general, how do I group by a calculated field?

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• I'm stuck in a basic Mongodb php tutorial

  - by p0larBoy

  I was following this tutorial : http://pronewb.com/mongodb-as-in-humongous-not-retarded. All was well until the "I feel the vibe" section. I do not know where to begin this section. Do i have to create a new php file or type it in some command line?

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• Random record from MongoDB

  - by Will M

  I am looking to get a random record from a huge (100 million record) mongodb. What is the fastest and most efficient way to do so? The data is already there and there are no field in which I can generate a random number and obtain a random row. Any suggestions?

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• MongoDB query against geospatial index with maxDistance fails from node.js client

  - by user1735497

  I want to query against a geospatial index in mongo-db (designed after this tutorial http://www.mongodb.org/display/DOCS/Geospatial+Indexing). So when I execute this from the shell everything works fine: db.sellingpoints.find(( { location : { $near: [48.190120, 16.270895], $maxDistance: 7 / 111.2 } } ); but the same query from my nodejs application (using mongoskin or mongoose), won't return any results until i set the distance-value to a very high number (5690) db.collection('sellingpoints') .find({ location: { $near: [lat,lng], $maxDistance: distance / 111.2} }) .limit(limit) .toArray(callback); Has someone any idea how to fix that?

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• MongoDB equivalent of SQL "OR"

  - by Matt

  So, MongoDB defaults to "AND" when finding records. For example: db.users.find({age: {'$gte': 30}, {'$lte': 40}}); The above query finds users = 30 AND <= 40 years old. How would I find users <= 30 OR = 40 years old?

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• MongoDB PHP Drive install failed (Windows)

  - by terence410

  I attempted to download the php_mongo.dll from this link (http://github.com/mongodb/mongo-php-driver/downloads) and added the extension to php. However it doesn't work at all. My PHP version is: 5.2.x Windows: Windows 7 64 bit. I have also try to use pecl install mongo but it returned some error like: This DSP mongo.dsp doesn't not exist. Could somebody help?

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• Symfony (PHP framework) and MongoDB ( or any json-based database)

  - by fenderplayer

  I was wondering if its possible to use a json-based schema-free, document-based database like Mongodb or Couchdb on a symfony project like its used for ruby-on-rails websites? And if yes, how can it be done?

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• mongodb java driver - raw command?

  - by Scott

  Is it possible to execute raw commands as javascript through the Java driver for MongoDB? I'm tired of wrapping everything in Java objects using Rhino, and would happily sacrifice performance for the convenience of passing javascript directly through to the DB. If not, I can always use sleepymongoose or something, but I don't really want to add yet another language (python) to the stack at this point. Any insights are appreciated.

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• MongoDB using NOT and AND together

  - by Stankalank

  I'm trying to negate an $and clause with MongoDB and I'm getting a MongoError: invalid operator: $and message back. Basically what I want to achieve is the following: query = { $not: { $and: [{institution_type:'A'}, {type:'C'}] } } Is this possible to express in a mongo query? Here is a sample collection: { "institution_type" : "A", "type" : "C" } { "institution_type" : "A", "type" : "D" } { "institution_type" : "B", "type" : "C" } { "institution_type" : "B", "type" : "D" } What I want to get back is the following: { "institution_type" : "A", "type" : "D" } { "institution_type" : "B", "type" : "C" } { "institution_type" : "B", "type" : "D" }

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• Indexing on only part of a field in MongoDB

  - by Rob Hoare

  Is there a way to create an index on only part of a field in MongoDB, for example on the first 10 characters? I couldn't find it documented (or asked about on here). The MySQL equivalent would be CREATE INDEX part_of_name ON customer (name(10));. Reason: I have a collection with a single field that varies in length from a few characters up to over 1000 characters, average 50 characters. As there are a hundred million or so documents it's going to be hard to fit the full index in memory (testing with 8% of the data the index is already 400MB, according to stats). Indexing just the first part of the field would reduce the index size by about 75%. In most cases the search term is quite short, it's not a full-text search. A work-around would be to add a second field of 10 (lowercased) characters for each item, index that, then add logic to filter the results if the search term is over ten characters (and that extra field is probably needed anyway for case-insensitive searches, unless anybody has a better way). Seems like an ugly way to do it though. [added later] I tried adding the second field, containing the first 12 characters from the main field, lowercased. It wasn't a big success. Previously, the average object size was 50 bytes, but I forgot that includes the _id and other overheads, so my main field length (there was only one) averaged nearer to 30 bytes than 50. Then, the second field index contains the _id and other overheads. Net result (for my 8% sample) is the index on the main field is 415MB and on the 12 byte field is 330MB - only a 20% saving in space, not worthwhile. I could duplicate the entire field (to work around the case insensitive search problem) but realistically it looks like I should reconsider whether MongoDB is the right tool for the job (or just buy more memory and use twice as much disk space). [added even later] This is a typical document, with the source field, and the short lowercased field: { "_id" : ObjectId("505d0e89f56588f20f000041"), "q" : "Continental Airlines", "f" : "continental " } Indexes: db.test.ensureIndex({q:1}); db.test.ensureIndex({f:1}); The 'f" index, working on a shorter field, is 80% of the size of the "q" index. I didn't mean to imply I included the _id in the index, just that it needs to use that somewhere to show where the index will point to, so it's an overhead that probably helps explain why a shorter key makes so little difference. Access to the index will be essentially random, no part of it is more likely to be accessed than any other. Total index size for the full file will likely be 5GB, so it's not extreme for that one index. Adding some other fields for other search cases, and their associated indexes, and copies of data for lower case, does start to add up, which I why I started looking into a more concise index.

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• SQL SERVER – Example of Performance Tuning for Advanced Users with DB Optimizer

  - by Pinal Dave

  Performance tuning is such a subject that everyone wants to master it. In beginning everybody is at a novice level and spend lots of time learning how to master the art of performance tuning. However, as we progress further the tuning of the system keeps on getting very difficult. I have understood in my early career there should be no need of ego in the technology field. There are always better solutions and better ideas out there and we should not resist them. Instead of resisting the change and new wave I personally adopt it. Here is a similar example, as I personally progress to the master level of performance tuning, I face that it is getting harder to come up with optimal solutions. In such scenarios I rely on various tools to teach me how I can do things better. Once I learn about tools, I am often able to come up with better solutions when I face the similar situation next time. A few days ago I had received a query where the user wanted to tune it further to get the maximum out of the performance. I have re-written the similar query with the help of AdventureWorks sample database. SELECT * FROM HumanResources.Employee e INNER JOIN HumanResources.EmployeeDepartmentHistory edh ON e.BusinessEntityID = edh.BusinessEntityID INNER JOIN HumanResources.Shift s ON edh.ShiftID = s.ShiftID; User had similar query to above query was used in very critical report and wanted to get best out of the query. When I looked at the query – here were my initial thoughts Use only column in the select statements as much as you want in the application Let us look at the query pattern and data workload and find out the optimal index for it Before I give further solutions I was told by the user that they need all the columns from all the tables and creating index was not allowed in their system. He can only re-write queries or use hints to further tune this query. Now I was in the constraint box – I believe * was not a great idea but if they wanted all the columns, I believe we can’t do much besides using *. Additionally, if I cannot create a further index, I must come up with some creative way to write this query. I personally do not like to use hints in my application but there are cases when hints work out magically and gives optimal solutions. Finally, I decided to use Embarcadero’s DB Optimizer. It is a fantastic tool and very helpful when it is about performance tuning. I have previously explained how it works over here. First open DBOptimizer and open Tuning Job from File >> New >> Tuning Job. Once you open DBOptimizer Tuning Job follow the various steps indicates in the following diagram. Essentially we will take our original script and will paste that into Step 1: New SQL Text and right after that we will enable Step 2 for Generating Various cases, Step 3 for Detailed Analysis and Step 4 for Executing each generated case. Finally we will click on Analysis in Step 5 which will generate the report detailed analysis in the result pan. The detailed pan looks like. It generates various cases of T-SQL based on the original query. It applies various hints and available hints to the query and generate various execution plans of the query and displays them in the resultant. You can clearly notice that original query had a cost of 0.0841 and logical reads about 607 pages. Whereas various options which are just following it has different execution cost as well logical read. There are few cases where we have higher logical read and there are few cases where as we have very low logical read. If we pay attention the very next row to original query have Merge_Join_Query in description and have lowest execution cost value of 0.044 and have lowest Logical Reads of 29. This row contains the query which is the most optimal re-write of the original query. Let us double click over it. Here is the query: SELECT * FROM HumanResources.Employee e INNER JOIN HumanResources.EmployeeDepartmentHistory edh ON e.BusinessEntityID = edh.BusinessEntityID INNER JOIN HumanResources.Shift s ON edh.ShiftID = s.ShiftID OPTION (MERGE JOIN) If you notice above query have additional hint of Merge Join. With the help of this Merge Join query hint this query is now performing much better than before. The entire process takes less than 60 seconds. Please note that it the join hint Merge Join was optimal for this query but it is not necessary that the same hint will be helpful in all the queries. Additionally, if the workload or data pattern changes the query hint of merge join may be no more optimal join. In that case, we will have to redo the entire exercise once again. This is the reason I do not like to use hints in my queries and I discourage all of my users to use the same. However, if you look at this example, this is a great case where hints are optimizing the performance of the query. It is humanly not possible to test out various query hints and index options with the query to figure out which is the most optimal solution. Sometimes, we need to depend on the efficiency tools like DB Optimizer to guide us the way and select the best option from the suggestion provided. Let me know what you think of this article as well your experience with DB Optimizer. Please leave a comment. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Joins, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• SQL Intersection Conference, Las Vegas MGM Grand 10-13 November 2014

  - by Paul White

  I am very pleased to announce that I will be speaking at the SQL Intersection conference in Las Vegas again this year. This time around, I am giving a full-day workshop, "Mastering SQL Server Execution Plan Analysis" as well as a two-part session, "Parallel Query Execution" during the main conference. The workshop is a pre-conference event, held on Sunday 9 November (straight after this year's PASS Summit). Being on Sunday gives you the whole Monday off to recover and before the...(read more)

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• sort mysql query by filtered query

  - by kalpaitch

  I have two mysql queries: $sql = "SELECT * FROM content WHERE threadName LIKE '%$filter%' ORDER BY lastUpdated desc"; and $sql = "SELECT * FROM content ORDER BY lastUpdated desc"; The end result is to have all rows returned from a particular table 'content' but have those that match the variable $filter at the top. Is there either a single query that could combine these two or should I be using a JOIN?

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• How to apply GROUP_CONCAT in mysql Query

  - by Query Master

  How to apply GROUP_CONCAT in this Query if you guys have any idea or any alternate solution about this please share me. Helps are definitely appreciated also (see Query or result required) Query SELECT WEEK(cpd.added_date) AS week_no,COUNT(cpd.result) AS death_count FROM cron_players_data cpd WHERE cpd.player_id = 81 AND cpd.result = 2 AND cpd.status = 1 GROUP BY WEEK(cpd.added_date); Query output result screen Result Required 23,24,25 AS week_no 2,3,1 AS death_count

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• MongoDB search in C#

  - by user3684208

  I have a problem with querying MongoDB. In my code I have a method Get which has as a parametar a Dictionary. It should go through the database and query it, comparing string and then object. So, i always get a problem with this object part, QueryDocument won't take in an object type because it isn't an BsonValue. I have tried to cast it but it won't work. Do you have any suggestions ? Thanks Code part : public List<ExceptionViewModel> Get(Dictionary<string, object> FilteredExceptions) { MongoClient mongo = new MongoClient(); MongoServer mongoServer = mongo.GetServer(); MongoDatabase db = mongoServer.GetDatabase("Aplikacija"); MongoCollection collection = db.GetCollection("Exceptions"); List<ExceptionViewModel> Get = new List<ExceptionViewModel>(); foreach (KeyValuePair<string,object> item in FilteredExceptions) { var query = new QueryDocument(item.Key.ToString(),item.Value); foreach (ExceptionViewModel exception in collection.FindAs<ExceptionViewModel>(query)) { Console.WriteLine("{0}", exception.BrowserName); } } return Get; }

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• SQL SERVER – Query Hint – Contest Win Joes 2 Pros Combo (USD 198) – Day 1 of 5

  - by pinaldave

  August 2011 we ran a contest where every day we give away one book for an entire month. The contest had extreme success. Lots of people participated and lots of give away. I have received lots of questions if we are doing something similar this month. Absolutely, instead of running a contest a month long we are doing something more interesting. We are giving away USD 198 worth gift every day for this week. We are giving away Joes 2 Pros 5 Volumes (BOOK) SQL 2008 Development Certification Training Kit every day. One copy in India and One in USA. Total 2 of the giveaway (worth USD 198). All the gifts are sponsored from the Koenig Training Solution and Joes 2 Pros. The books are available here Amazon | Flipkart | Indiaplaza How to Win: Read the Question Read the Hints Answer the Quiz in Contact Form in following format Question Answer Name of the country (The contest is open for USA and India residents only) 2 Winners will be randomly selected announced on August 20th. Question of the Day: Which of the following queries will return dirty data? a) SELECT * FROM Table1 (READUNCOMMITED) b) SELECT * FROM Table1 (NOLOCK) c) SELECT * FROM Table1 (DIRTYREAD) d) SELECT * FROM Table1 (MYLOCK) Query Hints: BIG HINT POST Most SQL people know what a “Dirty Record” is. You might also call that an “Intermediate record”. In case this is new to you here is a very quick explanation. The simplest way to describe the steps of a transaction is to use an example of updating an existing record into a table. When the insert runs, SQL Server gets the data from storage, such as a hard drive, and loads it into memory and your CPU. The data in memory is changed and then saved to the storage device. Finally, a message is sent confirming the rows that were affected. For a very short period of time the update takes the data and puts it into memory (an intermediate state), not a permanent state. For every data change to a table there is a brief moment where the change is made in the intermediate state, but is not committed. During this time, any other DML statement needing that data waits until the lock is released. This is a safety feature so that SQL Server evaluates only official data. For every data change to a table there is a brief moment where the change is made in this intermediate state, but is not committed. During this time, any other DML statement (SELECT, INSERT, DELETE, UPDATE) needing that data must wait until the lock is released. This is a safety feature put in place so that SQL Server evaluates only official data. Additional Hints: I have previously discussed various concepts from SQL Server Joes 2 Pros Volume 1. SQL Joes 2 Pros Development Series – Dirty Records and Table Hints SQL Joes 2 Pros Development Series – Row Constructors SQL Joes 2 Pros Development Series – Finding un-matching Records SQL Joes 2 Pros Development Series – Efficient Query Writing Strategy SQL Joes 2 Pros Development Series – Finding Apostrophes in String and Text SQL Joes 2 Pros Development Series – Wildcard – Querying Special Characters SQL Joes 2 Pros Development Series – Wildcard Basics Recap Next Step: Answer the Quiz in Contact Form in following format Question Answer Name of the country (The contest is open for USA and India) Bonus Winner Leave a comment with your favorite article from the “additional hints” section and you may be eligible for surprise gift. There is no country restriction for this Bonus Contest. Do mention why you liked it any particular blog post and I will announce the winner of the same along with the main contest. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Joes 2 Pros, PostADay, SQL, SQL Authority, SQL Puzzle, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• Which of CouchDB or MongoDB suits my needs?

  - by vonconrad

  Where I work, we use Ruby on Rails to create both backend and frontend applications. Usually, these applications interact with the same MySQL database. It works great for a majority of our data, but we have one situation which I would like to move to a NoSQL environment. We have clients, and our clients have what we call "inventories"--one or more of them. An inventory can have many thousands of items. This is currently done through two relational database tables, inventories and inventory_items. The problems start when two different inventories have different parameters: # Inventory item from inventory 1, televisions { inventory_id: 1 sku: 12345 name: Samsung LCD 40 inches model: 582903-4 brand: Samsung screen_size: 40 type: LCD price: 999.95 } # Inventory item from inventory 2, accomodation { inventory_id: 2 sku: 48cab23fa name: New York Hilton accomodation_type: hotel star_rating: 5 price_per_night: 395 } Since we obviously can't use brand or star_rating as the column name in inventory_items, our solution so far has been to use generic column names such as text_a, text_b, float_a, int_a, etc, and introduce a third table, inventory_schemas. The tables now look like this: # Inventory schema for inventory 1, televisions { inventory_id: 1 int_a: sku text_a: name text_b: model text_c: brand int_b: screen_size text_d: type float_a: price } # Inventory item from inventory 1, televisions { inventory_id: 1 int_a: 12345 text_a: Samsung LCD 40 inches text_b: 582903-4 text_c: Samsung int_a: 40 text_d: LCD float_a: 999.95 } This has worked well... up to a point. It's clunky, it's unintuitive and it lacks scalability. We have to devote resources to set up inventory schemas. Using separate tables is not an option. Enter NoSQL. With it, we could let each and every item have their own parameters and still store them together. From the research I've done, it certainly seems like a great alterative for this situation. Specifically, I've looked at CouchDB and MongoDB. Both look great. However, there are a few other bits and pieces we need to be able to do with our inventory: We need to be able to select items from only one (or several) inventories. We need to be able to filter items based on its parameters (eg. get all items from inventory 2 where type is 'hotel'). We need to be able to group items based on parameters (eg. get the lowest price from items in inventory 1 where brand is 'Samsung'). We need to (potentially) be able to retrieve thousands of items at a time. We need to be able to access the data from multiple applications; both backend (to process data) and frontend (to display data). Rapid bulk insertion is desired, though not required. Based on the structure, and the requirements, are either CouchDB or MongoDB suitable for us? If so, which one will be the best fit? Thanks for reading, and thanks in advance for answers. EDIT: One of the reasons I like CouchDB is that it would be possible for us in the frontend application to request data via JavaScript directly from the server after page load, and display the results without having to use any backend code whatsoever. This would lead to better page load and less server strain, as the fetching/processing of the data would be done client-side.

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• SQLAuthority News – Microsoft SQL Server 2005/2008 Query Optimization & Performance Tuning Training

  - by pinaldave

  Last 3 days to register for the courses. This is one time offer with big discount. The deadline for the course registration is 5th May, 2010. There are two different courses are offered by Solid Quality Mentors 1) Microsoft SQL Server 2005/2008 Query Optimization & Performance Tuning – Pinal Dave Date: May 12-14, 2010 Price: Rs. 14,000/person for 3 days Discount Code: ‘SQLAuthority.com’ Effective Price: Rs. 11,000/person for 3 days 2) SharePoint 2010 – Joy Rathnayake Date: May 10-11, 2010 Price: Rs. 11,000/person for 3 days Discount Code: ‘SQLAuthority.com’ Effective Price: Rs. 8,000/person for 2 days Download the complete PDF brochure. To register, either send an email to [email protected] or call +91 95940 43399. Feel free to drop me an email at pinal “at” SQLAuthority.com for any additional information and clarification. Training Venue: Abridge Solutions, #90/B/C/3/1, Ganesh GHR & MSY Plaza, Vittalrao Nagar, Near Image Hospital, Madhapur, Hyderabad – 500 081. Additionally there is special program of SolidQ India Insider. This is only available to first few registrants of the courses only. Read more details about the course here. Read my TechEd India 2010 experience here. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Training, SQLAuthority News, T SQL, Technology

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• SQL SERVER – Using MAXDOP 1 for Single Processor Query – SQL in Sixty Seconds #008 – Video

  - by pinaldave

  Today’s SQL in Sixty Seconds video is inspired from my presentation at TechEd India 2012 on Speed up! – Parallel Processes and Unparalleled Performance. There are always special cases when it is about SQL Server. There are always few queries which gives optimal performance when they are executed on single processor and there are always queries which gives optimal performance when they are executed on multiple processors. I will be presenting the how to identify such queries as well what are the best practices related to the same. In this quick video I am going to demonstrate if the query is giving optimal performance when running on single CPU how one can restrict queries to single CPU by using hint OPTION (MAXDOP 1). More on Errors: Difference Temp Table and Table Variable – Effect of Transaction Effect of TRANSACTION on Local Variable – After ROLLBACK and After COMMIT Debate – Table Variables vs Temporary Tables – Quiz – Puzzle – 13 of 31 I encourage you to submit your ideas for SQL in Sixty Seconds. We will try to accommodate as many as we can. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Video

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• “Query cost (relative to the batch)” <> Query cost relative to batch

  - by Dave Ballantyne

  OK, so that is quite a contradictory title, but unfortunately it is true that a common misconception is that the query with the highest percentage relative to batch is the worst performing.  Simply put, it is a lie, or more accurately we dont understand what these figures mean. Consider the two below simple queries: SELECT * FROM Person.BusinessEntity JOIN Person.BusinessEntityAddress ON Person.BusinessEntity.BusinessEntityID = Person.BusinessEntityAddress.BusinessEntityID go SELECT * FROM Sales.SalesOrderDetail JOIN Sales.SalesOrderHeader ON Sales.SalesOrderDetail.SalesOrderID = Sales.SalesOrderHeader.SalesOrderID After executing these and looking at the plans, I see this : So, a 13% / 87% split ,  but 13% / 87% of WHAT ? CPU ? Duration ? Reads ? Writes ? or some magical weighted algorithm ?  In a Profiler trace of the two we can find the metrics we are interested in. CPU and duration are well out but what about reads (210 and 1935)? To save you doing the maths, though you are more than welcome to, that’s a 90.2% / 9.8% split.  Close, but no cigar. Lets try a different tact.  Looking at the execution plan the “Estimated Subtree cost” of query 1 is 0.29449 and query 2 its 1.96596.  Again to save you the maths that works out to 13.03% and 86.97%, round those and thats the figures we are after.  But, what is the worrying word there ? “Estimated”.  So these are not “actual”  execution costs,  but what’s the problem in comparing the estimated costs to derive a meaning of “Most Costly”.  Well, in the case of simple queries such as the above , probably not a lot.  In more complicated queries , a fair bit. By modifying the second query to also show the total number of lines on each order SELECT *,COUNT(*) OVER (PARTITION BY Sales.SalesOrderDetail.SalesOrderID) FROM Sales.SalesOrderDetail JOIN Sales.SalesOrderHeader ON Sales.SalesOrderDetail.SalesOrderID = Sales.SalesOrderHeader.SalesOrderID The split in percentages is now 6% / 94% and the profiler metrics are : Even more of a discrepancy. Estimates can be out with actuals for a whole host of reasons,  scalar UDF’s are a particular bug bear of mine and in-fact the cost of a udf call is entirely hidden inside the execution plan.  It always estimates to 0 (well, a very small number). Take for instance the following udf Create Function dbo.udfSumSalesForCustomer(@CustomerId integer) returns money as begin Declare @Sum money Select @Sum= SUM(SalesOrderHeader.TotalDue) from Sales.SalesOrderHeader where CustomerID = @CustomerId return @Sum end If we have two statements , one that fires the udf and another that doesn't: Select CustomerID from Sales.Customer order by CustomerID go Select CustomerID,dbo.udfSumSalesForCustomer(Customer.CustomerID) from Sales.Customer order by CustomerID The costs relative to batch is a 50/50 split, but the has to be an actual cost of firing the udf. Indeed profiler shows us : No where even remotely near 50/50!!!! Moving forward to window framing functionality in SQL Server 2012 the optimizer sees ROWS and RANGE ( see here for their functional differences) as the same ‘cost’ too SELECT SalesOrderDetailID,SalesOrderId, SUM(LineTotal) OVER(PARTITION BY salesorderid ORDER BY Salesorderdetailid RANGE unbounded preceding) from Sales.SalesOrderdetail go SELECT SalesOrderDetailID,SalesOrderId, SUM(LineTotal) OVER(PARTITION BY salesorderid ORDER BY Salesorderdetailid Rows unbounded preceding) from Sales.SalesOrderdetail By now it wont be a great display to show you the Profiler trace reads a *tiny* bit different. So moral of the story, Percentage relative to batch can give a rough ‘finger in the air’ measurement, but dont rely on it as fact.

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