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Trying to get an UPSERT working on a set of data using dapper

I'm trying to get an upsert working on a collection of IDs (not the primary key - that's an identity int column) on a table using dapper. This doesn't need to be a dapper function, just including in case that helps.
I'm wondering if it's possible (either through straight SQL or using a dapper function) to run an upsert on a collection of IDs (specifically an IEnumerable of ints).
I really only need a simple example to get me started, so an example would be:
I have three objects of type Foo:
{ "ExternalID" : 1010101, "DescriptorString" : "I am a descriptive string", "OtherStuff" : "This is some other stuff" }
{ "ExternalID" : 1010122, "DescriptorString" : "I am a descriptive string123", "OtherStuff" : "This is some other stuff123" }
{ "ExternalID" : 1033333, "DescriptorString" : "I am a descriptive string555", "OtherStuff" : "This is some other stuff555" }
I have a table called Bar, with those same column names (where only 1033333 exists):
Table Foo
Column ID | ExternalID | DescriptorString | OtherStuff
Value [1]|[1033333] |["I am a descriptive string555"]|["This is some other stuff555"]

Well, since you said that this didn't need to be dapper-based ;-), I will say that the fastest and cleanest way to get this data upserted is to use Table-Valued Parameters (TVPs) which were introduced in SQL Server 2008. You need to create a User-Defined Table Type (one time) to define the structure, and then you can use it in either ad hoc queries or pass to a stored procedure. But this way you don't need to export to a file just to import, nor do you need to convert it to XML just to convert it back to a table.
Rather than copy/paste a large code block, I have noted three links below where I have posted the code to do this (all here on S.O.). The first two links are the full code (SQL and C#) to accomplish this (the 2nd link being the most analogous to what you are trying to do). Each is a slight variation on the theme (which shows the flexibility of using TVPs). The third is another variation but not the full code as it just shows the differences from one of the first two in order to fit that particular situation. But in all 3 cases, the data is streamed from the app into SQL Server. There is no creating of any additional collection or external file; you use what you currently have and only need to duplicate the values of a single row at a time to be sent over. And on the SQL Server side, it all comes through as a populated Table Variable. This is far more efficient than taking data you already have in memory, converting it to a file (takes time and disk space) or XML (takes cpu and memory) or a DataTable (for SqlBulkCopy; takes cpu and memory) or something else, only to rely on an external factor such as the filesystem (the files will need to be cleaned up, right?) or need to parse out of XML.
How can I insert 10 million records in the shortest time possible?
Pass Dictionary<string,int> to Stored Procedure T-SQL
Storing a Dictionary<int,string> or KeyValuePair in a database
Now, there are some issues with the MERGE command (see Use Caution with SQL Server's MERGE Statement) that might be a reason to avoid using it. So, I have posted the "upsert" code that I have been using for years to an answer on DBA.StackExchange:
How to avoid using Merge query when upserting multiple data using xml parameter?

Storing precedence of operations in database? Patterns?

I have a need to store a list of operations and their precedence or order in the database.
I am unsure whether to store operations with the highest precedence as ZERO or otherwise.
In other words,
should the order of operations in precedence be stored in the database as :
'0 1 2 3 4 5 6'
OR
'6 5 4 3 2 1 0'
TABLE DATA STRUCTURE:
[operationName, precedence]
Also, a user can re-order them etc from the UI(a WPF app) in a list and hit "Save", in which case I will need to update them. He can also create a new operation and insert it into the list in the UI and hit SAVE ... which should also store the operations in the database according to the order in the UI.
EDIT:
Other things are they can even remove or delete them from the UI which needs to be updated to the database as well.
Are there any best practices or patterns surrounding this?
Thanks

It's very simple. Looks like you have a list of items that you need to save. You also need to sort the items by a user-defined order. A user can change order of items, can remove items etc. You want this to be persisted to a database.
Suppose you have a table in a database that stores your items. Just now there is nothing to store a user-defined order. What you need to add is a single property to the type (and a single column to the relation database's table) to reflect an order.
id | operation_name | user_order
--------------------------------
So when user reorders items, you save all of them back to the database, or alternatively execute an UPDATE statement and update the user_order column.
Basically, this is what you have just now. When you query your data, you can use this SQL
Select ...
From ...
Order by user_order
or the same in LINQ

This looks like an audit trailing facility. If those sequences represent some dates then Event sourcing by Martin Fowler could show you some patterns:
Event Sourcing

SQL Server recommendation for storing segmented gl account codes in database

I've been tasked with an enhancement to our order system that will require importing segmented GL account codes for assignment on individual line items of an order.
I need to support querying the codes by segment1, segment2, etc in order to load cascading dropdown boxes for assignment by the user. The GL codes will have one or more segments delimited by a character. An example of a code is "1010.1034001.99.01".
I've loaded several thousand codes into a table for testing where the entire string value exists in one column (delimited by a character). I've created two variations of functions that return rows where segment1 value is equal to some parameter. The query also supports further querying by providing additional parameters for other segment values.
I intend to support these queries from the table using Entify Framework 6, but used sql functions to get a feel for what the performance may be when the GL account codes are stored in one column. Performance was not as good as I had hoped.
Does anyone have recommendations on how best to store this data (there may be 200,000 codes). Do you feel that I can query using EF and expect performant results?
Would a hierarchy organization make more sense for this data? Our team was hopeful to store the delimited values on one column.
Thanks in advance.

If you would use a table with three columns you could store the values cascading, enabling you to make your queries a lot easier and probably faster. Why would your team hope to store it in one column, what advantage does that have?
if you have
ID
Code
ParentCodeId
where ID is a unique key and ParentCodeId is a nullable reference to that unique Id you can split your exaple code as follows:
ID Code Parent
1 1010 null
2 1034001 1
3 99 2
4 01 3
By applying some logic when importing your codes, you can check if a code already exists as a parent on the needed level so you don;t have to repeat them, and that way you coul dget all codes that start with 10100 by selecting on selectiong on parentID 1.

High performance Custom user fields

looking for examples/tutorial for custom user fields, not via EAV
EAV is going to be problematic for various reasons such as performance
there are many base entities/tables with over 100000 records each
there will likely be over a dozen attributes
the records are to be displayed in a flat ui grid incl. custom fields so flattening them would be an issue while maintaining performance
Looking at enabling this via DDL where all custom fields would go into a matching table such as
<tablename>_custom_<userid>
and all user attributes would map to a column each and all their metadata stored in a metadata table
the retrieval would be simpler where the query would simply be
select *
from <tablename> A, tableName_custom_userid B
where B.KeyField = A.KeyField --( perhaps using outer join, haven't gone that far yet )
Wondering if there are any gotchas down the road that i need to be aware of ?
of course any samples/pointers would be helpful to kickstart the effort
specifically would appreciate any advice on using DDL for Sql Server compact 4

One technique I have seen used is to use a sort of 'hard-coded' EAV pattern. Don't hang up! It worked well with the dataset sizes you were talking about and didn't actually use EAV - it was only EAV-esque.
The idea is to have a set of tables to store these custom attributes within it, with some triggers (described below) on them. The custom attributes tablesets store metadata about the attribute (what table it goes with, data type, constraints, etc). You can get very fancy with this but I did not haev the need.
The triggers on your meta-tables are there to re-generate views that rollup base+extension into first class objects within the DB. So instead of table person + employee extension table, you have an employee view that includes both. When you drop a new value into the custom attributes tables, the triggers will re-roll the views and include the new stuff. If you wanted to go nuts, you could also have the triggers re-write stored procedures as well. Depending on how your mid-tier code is structured, you would still be forced to re-code some, however this would be the case anyway should you be applying rules that read the data.
In testing, I found that for the relatively small # of records you're talking about, performance was somewhat slower but followed roughly the same pattern of degradation (2x the number of records, ~2x as slow).
-- edits --
How I saw it done, you had a table that represented your first class objects, so a row for 'person' and a row for 'employee,' etc. We'll call that FCO. Then you had a secondary table that stored what tables represented the FCO. We'll call that Srcs.. For person, there would be one row, which is the person table. For Employee, there would be two rows, the person table and the Employee extension. There is a third table, called Attribs, which stores the columns from the tables that constitute the FCO. For simplicity, we'll say Employee has ID, Name and Address, and Employee has Hire Date and Department, and obviously PersonID referring back to Person table. So, 2 rows in FCO table (person and employee), 3 rows in Src table, 8 rows in Attribs.
The view, we'll call it vw_Employee, selects PersonID, Name, Address, Hire Date, Department from the two tables. It is built by a SQL stored procedure we'll call OnMetadataChange.
This SP is fired (by trigger or batch process), and its purpose is to generate the CREATE VIEW statements. It will iterate through every First Class Object, collect which fields from which tables constitute the view, and will issue a CREATE statement based on that. So OnMetadataChange produces a DROP and CREATE for each view, it generates a dynamic SQL statement that is executed once per entry in FCO table. It is preferable to do this with Triggers but not necessary. Hopefully your FCO definitions won't change too often, and when they do, there will probably be a code release as well. You can run your OnMetadataChange SP at that time.
The end result is a 2-layer database. The views constitute the First Class Object layer, which is meaningful to the application. The application only uses views. The tables constitute the 'physical' layer, which the application shouldn't care about. The meta-tables are essentially your mapping between the FCO layer and the physical layer. It takes some time to set it up, but it's quite effective, and gives you many of the benefits of EAV, while at the same time giving you the concrete benefits of 3nf tables (indexability, etc).
If you'd like I can throw some sample SQL out there.

Part of the problem you are having is that you are trying to store schema-less data in a SQL database, which is not its strength. There are three approaches that would make your life far easier:
1) Have a column which stores the serialized custom fields, with whatever format is mst convenient. For example, this column could store xml. Upsides are that you can use SQL Server Compact and pulling back a record is trivial. Downsides are that you always have to pull/push the entire xml blob to do an update, and it is difficult to impossible to query on any custom fields.
2) Upgrade to SQL Server Express, and use XML columns. This is nearly the same as the first suggestion, except that any server ready version of SQL Server has native support for XML data. These columns can have indexes added and fields within the data can be used in queries.
3) Use a Schema-less Database, like MongoDB or CouchDB. These databases are all about storing schemaless data, so your custom fields will be no different than any other field. As such, you can index and query custom fields. Upsides are that custom data is incredibly easy to work with, downsides are that you would have to spend some time rethinking how you store data to fit within their model.
If you do not need to query based on custom fields, or if you can query custom fields within business logic, then the first option can work for you. In any other case, I would err towards something with more capabilities than compact. If cost is the deciding factor, both SQL Server Express and MongoDB are free.

dynamic data model

I have a project that requires user-defined attributes for a particular object at runtime (Lets say a person object in this example). The project will have many different users (1000 +), each defining their own unique attributes for their own sets of 'Person' objects.
(Eg - user #1 will have a set of defined attributes, which will apply to all person objects 'owned' by this user. Mutliply this by 1000 users, and that's the bottom line minimum number of users the app will work with.) These attributes will be used to query the people object and return results.
I think these are the possible approaches I can use. I will be using C# (and any version of .NET 3.5 or 4), and have a free reign re: what to use for a datastore. (I have mysql and mssql available, although have the freedom to use any software, as long as it will fit the bill)
Have I missed anything, or made any incorrect assumptions in my assessment?
Out of these choices - what solution would you go for?
Hybrid EAV object model. (Define the database using normal relational model, and have a 'property bag' table for the Person table).
Downsides: many joins per / query. Poor performance. Can hit a limit of the number of joins / tables used in a query.
I've knocked up a quick sample, that has a Subsonic 2.x 'esqe interface:
Select().From().Where ... etc
Which generates the correct joins, then filters + pivots the returned data in c#, to return a datatable configured with the correctly typed data-set.
I have yet to load test this solution. It's based on the EA advice in this Microsoft whitepaper:
SQL Server 2008 RTM Documents Best Practices for Semantic Data Modeling for Performance and Scalability
Allow the user to dynamically create / alter the object's table at run-time. This solution is what I believe NHibernate does in the background when using dynamic properties, as discussed where
http://bartreyserhove.blogspot.com/2008/02/dynamic-domain-mode-using-nhibernate.html
Downsides:
As the system grows, the number of columns defined will get very large, and may hit the max number of columns. If there are 1000 users, each with 10 distinct attributes for their 'Person' objects, then we'd need a table holding 10k columns. Not scalable in this scenario.
I guess I could allow a person attribute table per user, but if there are 1000 users to start, that's 1000 tables plus the other 10 odd in the app.
I'm unsure if this would be scalable - but it doesn't seem so. Someone please correct me if I an incorrect!
Use a NoSQL datastore, such as CouchDb / MongoDb
From what I have read, these aren't yet proven in large scale apps, based on strings, and are very early in development phase. IF I am incorrect in this assessment, can someone let me know?
http://www.eflorenzano.com/blog/post/why-couchdb-sucks/
Using XML column in the people table to store attributes
Drawbacks - no indexing on querying, so every column would need to be retrieved and queried to return a resultset, resulting in poor query performance.
Serializing an object graph to the database.
Drawbacks - no indexing on querying, so every column would need to be retrieved and queried to return a resultset, resulting in poor query performance.
C# bindings for berkelyDB
From what I read here: http://www.dinosaurtech.com/2009/berkeley-db-c-bindings/
Berkeley Db has definitely proven to be useful, but as Robert pointed out – there is no easy interface. Your entire wOO wrapper has to be hand coded, and all of your indices are hand maintained. It is much more difficult than SQL / linq-to-sql, but that’s the price you pay for ridiculous speed.
Seems a large overhead - however if anyone can provide a link to a tutorial on how to maintain the indices in C# - it could be a goer.
SQL / RDF hybrid.
Odd I didn't think of this before. Similar to option 1, but instead of an "property bag" table, just XREF to a RDF store?
Querying would them involve 2 steps - query the RDF store for people hitting the correct attributes, to return the person object(s), and use the ID's for these person object in the SQL query to return the relational data. Extra overhead, but could be a goer.

The ESENT database engine on Windows is used heavily for this kind of semi-structured data. One example is Microsoft Exchange which, like your application, has thousands of users where each user can define their own set of properties (MAPI named properties). Exchange uses a slightly modified version of ESENT.
ESENT has a lot of features that enable applications with large meta-data requirements: each ESENT table can have about ~32K columns defined; tables, indexes and columns can be added at runtime; sparse columns don't take up any record space when not set; and template tables can reduce the space used by the meta-data itself. It is common for large applications to have thousands of tables/indexes.
In this case you can have one table per user and create the per-user columns in the table, creating indexes on any columns that you want to query. That would be similar to the way that some versions of Exchange store their data. The downside of this approach is that ESENT doesn't have a query engine so you will have to hand-craft your queries as MakeKey/Seek/MoveNext calls.
A managed wrapper for ESENT is here:
http://managedesent.codeplex.com/

In a EAV model you don't have to have many joins, as you can just have the joins you need for the query filtering. For the resultset, return property entries as a separate rowset.
That is what we are doing in our EAV implementation.
For example, a query might return persons with extended property 'Age' > 18:
Properties table:
1 Age
2 NickName
First resultset:
PersonID Name
1 John
2 Mary
second resultset:
PersonID PropertyID Value
1 1 24
1 2 'Neo'
2 1 32
2 2 'Pocahontas'
For the first resultset, you need an inner join for the 'age' extended property
to query the basic Person object entity part:
select p.ID, p.Name from Persons p
join PersonExtendedProperties pp
on p.ID = pp.PersonID
where pp.PropertyName = 'Age'
and pp.PropertyValue > 18 -- probably need to convert to integer here
For the second resultset, we are making an outer join of the first resultset with PersonExtendedProperties table to get the rest of the extended properties. It's a 'narrow' resultset, we do not pivot the properties in sql, so we don't need multiple joins here.
Actually we use separate tables for different types to avoid data type conversion, to have extended properties indexed and easily queriable.

My recommendation:
Allow properties to be marked as indexable. Have a smallish hard limit on number of indexable properties, and on columns per object. Have a large hard limit on total column types in all objects.
Implement indexes as separate tables (one per index) joined with main table of data (main table has large unique key for object). (Index tables can then be created/dropped as required).
Serialize the data, including the index columns, plus put the index propertoes in first class relational columns in their dedicated index tables. Use JSON instead of XML to save space in the table. Enforce short column name policy (or long display name and short stored name policy) to save space and increase performance.
Use quarks for field identifiers (but only in the main engine to save RAM and speed some read operations -- don't rely on quark pointer comparison in all cases).
My thought on your options:
1 is a possible. Performance clearly will be lower than if field ID columns not stored.
2 is a no in general DB engines not all happy about dynamic schema changes. But a possible yes if your DB engine is good at this.
3 Possible.
4 Yes though I'd use JSON.
5 Seems like 4 only less optimized??
6 Sounds good; would go with if happy to try something new and also if happy about reliability and performance but usually would want to go with more mainstream technology. I'd also like to reduce the number of engines involved in coordinating a transaction to less then would be true here.
Edit: But of course though I've recommened something there can be no general right answer here -- profile various data models and approaches with your data to see what runs best for your application.
Edit: Changed last edit wording.

Assuming you an place a limit, N, on how many custom attributes each user can define; just add N extra columns to the Person table. Then have a separate table where you store per-user metadata to describe how to interpret the contents of those columns for each user. Similar to #1 once you've read in the data, but no joins needed to pull in the custom attributes.

For a problem similar to your problem, we have used the "XML Column" approach (the fourth one in your survey of methods). But you should note that many databases (DBMS) support index for xml values.
I recommend you to use one table for Person which contains one xml column along with other common columns. In other words, design the Person table with columns that are common for all person records and add a single xml column for dynamic and differing attributes.
We are using Oracle. it supports index for its xml-type. Two types of indices are supported: 1- XMLIndex for indexing elements and attributes within an xml, 2- Oracle Text Index for enabling full-text search in text fields of the xml.
For example, in Oracle you can create an index such as:
CREATE INDEX index1 ON table_name (XMLCast(XMLQuery ('$p/PurchaseOrder/Reference'
PASSING XML_Column AS "p" RETURNING CONTENT) AS VARCHAR2(128)));
and xml-query is supported in select queries:
SELECT count(*) FROM purchaseorder
WHERE XMLCast(XMLQuery('$p/PurchaseOrder/Reference'
PASSING OBJECT_VALUE AS "p" RETURNING CONTENT)
AS INTEGER) = 25;
As I know, other databases such as PostgreSQL and MS SQL Server (but not mysql) support such index models for xml value.
see also:
http://docs.oracle.com/cd/E11882_01/appdev.112/e23094/xdb_indexing.htm#CHDEADIH