API - How to programmatically merge a list of merge candidates returned by .VersionControlServer.GetMergeCandidates? - api

I am creating a clone of Default Merge Window, to add a feature.
I already have a Merge candidates in a grid from command below:
MergeCandidate[] candidates = tfs.GetMergeCandidates(edtSelectedSource.Text, cbxTargetBranchs.Text);
Now, the user selected 1 or more candidates and I need to merge them.
But the TFS API VersionControl.Merge requires source path and target path.
At first, my question, I need to iterate each candidate and merge each file of its changesets, one by one ?
Second, how could I obtains the target path from a changeset ?


First off, I've done a fair amount of programming with the TFS API, but merging is something that I would never blindly trust to automation. Merge conflicts are best dealt with by human beings. Yes, it's painful and can be automated in many cases, but in many others - things can go terribly wrong. I would think twice and then twice again before doing this on Production branches.
Here's some tips that should help:
You need to create a temp Workspace. The Workspace is the sandbox where everything happens. The Workspace can have files and thus, file locations associated with it. Workspace items have rich metadata.
Have a look at the Workspace and WorkspaceInfo classes.
Then have a look at the workspace client:
http://msdn.microsoft.com/en-us/library/microsoft.teamfoundation.versioncontrol.client.item.aspx


As long as the changesets are continuous, you can do it in a single merge call. If they are not continuous, you need to submit n merges for each continuous block. Let's say they select changesets 10, 15 and 20 and these are continuous (i.e. there are no additional candidates between that range) then you would submit a merge with a versionFrom of 10 and versionTo of 20.
As far as paths go, you want to use the ones that you passed into QueryMergeCandidates and you'll want to specify the full recursion type as well.

Related

Multiple users executing the same workflow

Are there guidelines regarding how to share a Snakemake workflow among multiple users on the same data under Linux, or is the whole thing considered bad practice?
Let me explain in case it's not clear:
Suppose user A executes a workflow in directory dir/. Assume the workflow terminates successfully, and he/she then properly sets file/directory permissions recursively on all output and intermediate files and the .snakemake/ subdirectory for other users to read/write, of course.
User B subsequently navigates to dir/, adds input files to the workflow, then executes it. Can anything go wrong?
TL;DR: I'm asking about non-concurrent execution of the same workflow by distinct users on the same system, and on the same data on disk. Is Snakemake designed for such use cases?

It's possible to run snakemake --nolock which will prevent locking of the directory, so multiple runs can be made from inside the same directory. However, without lock, there's now an opening for errors due to concurrent runs trying to modify the same files. It's probably OK, if you are certain that this will be avoided, e.g. if you are in constant communication with another user about which files will be modified.
An alternative option is to create a third directory/path, and put all the data there. This way you can work from separate directories/path and avoid costly recomputes.

I would say that from the point of view of snakemake, and workflow management in general, it's ok for user B to add or update input files and re-run the pipeline. After all, one of the advantages of a workflow management system is to update results according to new input. The problem is that user A could find her results updated without being aware of it.
From the top of my head and without more detail this is what I would suggest. Make snakemake read the list of input files from a table (pandas comes in handy for this) or from some configuration file. Keep this sample sheet under version control (with git/github) together with the Snakefile and other source code.
When users update the working directory with new files, they will also need to update the sample sheet in order for snakemake to "see" the new input and other users will know about it via version control. I prefer this setup over dumping files in a directory and letting snakemake process whatever is in there.

Work Item Query Policy to check workitems match on merge

With our TFS 2015 source control we require developers to check-in changes against work items.
However, we've had a couple of instances where a developer has checked in against one work item within our development branch, but then when merging to our QA branch they've checked in the merged changes to a different work item. An example of this is where a bug has been created underneath a PBI, the changes in dev have been checked in against a task under the bug, but then merged to QA against the PBI itself. This causes us issues with traceability.
I've seen that it's possible to add a check-in policy of "Work Item Query Policy". I'm just wondering if there is a way to write a query that will determine if the work item of a check-in after a merge matches the work item of the source changesets? I'm not necessarily after the exact query (though it would be lovely if someone could provide one :) ), really I'm just wondering whether it's possible or not to have a query to do this - i.e. is the information available to queries in TFS?

You can't do this with the existing policies, you'd need to build a custom policy.
So, technically this is possible. You can access the VersionControlServer object through the PendingChanges object:
this.PendingCheckin.PendingChanges.Workspace.VersionControlServer
You can use that to query the history of the branch in question and grab the work items associated to the check-ins in that branch.
You can check the associated workitems to the current workitem:
this.PendingCheckin.WorkItems
You could probably even provide the option to auto-correct by adding the correct work items to the checkin upon validation.
One of my policies provides an example on using the VersionControlServer from a policy.

What's a best approach to create a filestore

This is an open ended question. I have noob understanding of databases but willing to learn whatever is required. Though I believe my problem could be done without learning a lot.
So, here goes the question:
I have large amount of files getting generated in mt projects(depending on the builds) and I need to archive them and also need to reproduce them according to buildNumber if requested by users. I don't expect these requests to be a lot. May be 1-2 requests a day.
For eg: 16GB data per build every week. Most of the files in weekly builds are duplicate. And I don't want to archive them again and again. I prefer to store them only once. There is one caveat that it can happen that the files relative location can change, even though content hasn't changed.
My approach is as follow: Create a hash from each file. Create the key-value pair as fileHash-actual file and store it. Store this information in some kind of manifest file for each build. So, I should be able to create the builds back with correct files/paths etc.
Can it ever happen that 2 different files will ever have the same hash? Can some database help to do it efficiently? I am currently thinking of dumping all files in one folder.
Thanks

Check for multiple files

Okay, I'll try to explain as good as I can... Quite a particular case.
Tools: SSIS 2008
We have a control flow that now needs to be triggered by an event: the presence of one or multiple files. (1,2 or 3)
The variables used:
BO_FileLocation_1
BO_FileLocation_2
BO_FileLocation_3
BO_FileName_1
BO_FileName_2
BO_FileName_3
There can be one, two or three files: defined in above variables. When they are filled in,
they should be processed. When they are empty, this means there's just one file file, the process should ignore them and jump to the next (file watcher?) task.
For example:
BO_FileLocation_1= "C:\"
BO_FileLocation_2 NULL
BO_FileLocation_3 NULL
BO_FileName_1= "test.csv"
BO_FileName_2 NULL
BO_FileName_3 NULL
The report only needs one file.
I'd need a generic concept that checks the presence of these files, it could be more generic than my SSIS knowledge can handle right now. For example handy, when there's a 4th file in the future. I was also thinking to work with a single script to handle all the logic.
Thanks in advance
A possibly irrelevant image:

If all you want is to trigger the Copy Source File to handle if one or more of the files is present, just use the OR Constraint in your flow. The following image shows you how:
First connect all to the destination:
Then click one of the green arrows. This will make its properties window pop up. Select the Logical ORinstead of the Logical AND:
If everything went well, you should now see the connections as dashed lines:

There are several possible solutions:
Create a sequence container and include all the file imports in the sequence container. Add int variables for RowCountFile1, RowCountFile2, and RowCountFile3 and set the value to 0 (this is the default value when you create an int variable). Add a RowCount transformation to each of the data flows. Create a precedence constraint from the sequence container to the "Do something" task. Set the precedence constraint to success and expression. Set the expression value to #RowCountFile1 > 0 || #RowCountFile2 > 0 || #RowCountFile3 > 0. The advantage of this approach is that you can take an action as soon as the files are detected, you import all available files, and you only take an action after all the files have been imported. You could then schedule running this SSIS package as a SQL Server Agent job step and run it as frequently as you want.
A variant on solution 1 is to use for each file enumerator containers inside the sequence container. This would be useful if you don't know the exact name of the file and you expect to import more than one under some circumstances. For instance, if you get a file every few minutes with a timestamp in its file name and your process doesn't run for some reason, then you may have to process multiple files to get caught up and then take an action once it has been done.
You could use the file watcher task as you outlined in your question. The only problem I have with the file watcher task is that the package has to be in a constantly running state. This makes it hard to troubleshoot problems and performance. It also can introduce other problems since I remember having some problems with the file watcher task years ago when it first came out. It may well be a totally stable task now, but I prefer other methods over the task after having been burned previously. If you really want the package to run continously instead of having it be called by a job, then you could always use a script task to check for file, sleep thread if not found, check again, etc. I'm sure that's what the file watcher task does, but I would trust my own C# over the task. Power to anyone who has had better experiences than me with File Watcher...
Use PowerShell. If you just want to take an action if a file appears and you aren't importing the data, then a PowerShell script could do this just as well as a SSIS package. The drawback is that you have to learn some basic PowerShell, it may be hard to maintain in the future since PowerShell is probably not your bread and butter core language, and you may have to rewrite the code again to a SSIS package if you want to import the data. You would probably call the PowerShell script from a SQL Server Agent job step, so scheduling can be handled pretty easily.
There are more options than what I listed, so let me know if you still want more suggestions.

Do you put your database static data into source-control ? How?

I'm using SQL-Server 2008 with Visual Studio Database Edition.
With this setup, keeping your schema in sync is very easy. Basically, there's a 'compare schema' tool that allow me to sync the schema of two databases and/or a database schema with a source-controlled creation script folder.
However, the situation is less clear when it comes to data, which can be of three different kind :
static data referenced in the code. typical example : my users can change their setting, and their configuration is stored on the server. However, there's a system-wide default value for each setting that is used in case the user didn't override it. The table containing those default settings grows as more options are added to the program. This means that when a new feature/option is checked in, the system-wide default setting is usually created in the database as well.
static data. eg. a product list populating a dropdown list. The program doesn't rely on the existence of a specific product in the list to work. This can be for example a list of unicode-encoded products that should be deployed in production when the new "unicode version" of the program is deployed.
other data, ie everything else (logs, user accounts, user data, etc.)
It seems obvious to me that my third item shouldn't be source-controlled (of course, it should be backuped on a regular basis)
But regarding the static data, I'm wondering what to do.
Should I append the insert scripts to the creation scripts? or maybe use separate scripts?
How do I (as a developer) warn the people doing the deployment that they should execute an insert statement ?
Should I differentiate my two kind of data? (the first one being usually created by a dev, while the second one is usually created by a non-dev)
How do you manage your DB static data ?

I have explained the technique I used in my blog Version Control and Your Database. I use database metadata (in this case SQL Server extended properties) to store the deployed application version. I only have scripts that upgrade from version to version. At startup the application reads the deployed version from the database metadata (lack of metadata is interpreted as version 0, ie. nothing is yet deployed). For each version there is an application function that upgrades to the next version. Usually this function runs an internal resource T-SQL script that does the upgrade, but it can be something else, like deploying a CLR assembly in the database.
There is no script to deploy the 'current' database schema. New installments iterate trough all intermediate versions, from version 1 to current version.
There are several advantages I enjoy by this technique:
Is easy for me to test a new version. I have a backup of the previous version, I apply the upgrade script, then I can revert to the previous version, change the script, try again, until I'm happy with the result.
My application can be deployed on top of any previous version. Various clients have various deployed version. When they upgrade, my application supports upgrade from any previous version.
There is no difference between a fresh install and an upgrade, it runs the same code, so I have fewer code paths to maintain and test.
There is no difference between DML and DDL changes (your original question). they all treated the same way, as script run to change from one version to next. When I need to make a change like you describe (change a default), I actually increase the schema version even if no other DDL change occurs. So at version 5.1 the default was 'foo', in 5.2 the default is 'bar' and that is the only difference between the two versions, and the 'upgrade' step is simply an UPDATE statement (followed of course by the version metadata change, ie. sp_updateextendedproperty).
All changes are in source control, part of the application sources (T-SQL scripts mostly).
I can easily get to any previous schema version, eg. to repro a customer complaint, simply by running the upgrade sequence and stopping at the version I'm interested in.
This approach saved my skin a number of times and I'm a true believer now. There is only one disadvantage: there is no obvious place to look in source to find 'what is the current form of procedure foo?'. Because the latest version of foo might have been upgraded 2 or 3 versions ago and it wasn't changed since, I need to look at the upgrade script for that version. I usually resort to just looking into the database and see what's in there, rather than searching through the upgrade scripts.
One final note: this is actually not my invention. This is modeled exactly after how SQL Server itself upgrades the database metadata (mssqlsystemresource).

If you are changing the static data (adding a new item to the table that is used to generate a drop-down list) then the insert should be in source control and deployed with the rest of the code. This is especially true if the insert is needed for the rest of the code to work. Otherwise, this step may be forgotten when the code is deployed and not so nice things happen.
If static data comes from another source (such as an import of the current airport codes in the US), then you may simply need to run an already documented import process. The import process itself should be in source control (we do this with all our SSIS packages), but the data need not be.

Here at Red Gate we recently added a feature to SQL Data Compare allowing static data to be stored as DML (one .sql file for each table) alongside the schema DDL that is currently supported by SQL Compare.
To understand how this works, here is a diagram that explains how it works.
The idea is that when you want to push changes to your target server, you do a comparison using the scripts as the source data source, which generates the necessary DML synchronization script to update the target. This means you don't have to assume that the target is being recreated from scratch each time. In time we hope to support static data in our upcoming SQL Source Control tool.
David Atkinson, Product Manager, Red Gate Software

I have come across this when developing CMS systems.
I went with appending the static data (the stuff referenced in the code) to the database creation scripts, then a separate script to add in any 'initialisation data' (like countries, initial product population etc).

For the first two steps, you could consider using an intermediate format (ie XML) for the data, then using a home grown tool, or something like CodeSmith to generate the SQL, and possible source files as well, if (for example) you have lookup tables which relate to enumerations used in the code - this helps enforce consistency.
This has another benefit that if the schema changes, in many cases you don't have to regenerate all your INSERT statements - you just change the tool.

I really like your distinction of the three types of data.
I agree for the third.
In our application, we try to avoid putting in the database the first, because it is duplicated (as it has to be in the code, the database is a duplicate). A secondary benefice is that we need no join or query to get access to that value from the code, so this speed things up.
If there is additional information that we would like to have in the database, for example if it can be changed per customer site, we separate the two. Other tables can still reference that data (either by index ex: 0, 1, 2, 3 or by code ex: EMPTY, SIMPLE, DOUBLE, ALL).
For the second, the scripts should be in source-control. We separate them from the structure (I think they typically are replaced as time goes, while the structures keeps adding deltas).
How do I (as a developer) warn the people doing the deployment that they should execute an insert statement ?
We have a complete procedure for that, and a readme coming with each release, with scripts and so on...

First off, I have never used Visual Studio Database Edition. You are blessed (or cursed) with whatever tools this utility gives you. Hopefully that includes a lot of flexibility.
I don't know that I'd make that big a difference between your type 1 and type 2 static data. Both are sets of data that are defined once and then never updated, barring subsequent releases and updates, right? In which case the main difference is in how or why the data is as it is, and not so much in how it is stored or initialized. (Unless the data is environment-specific, as in "A" for development, "B" for Production. This would be "type 4" data, and I shall cheerfully ignore it in this post, because I've solved it useing SQLCMD variables and they give me a headache.)
First, I would make a script to create all the tables in the database--preferably only one script, otherwise you can have a LOT of scripts lying about (and find-and-replace when renaming columns becomes very awkward). Then, I would make a script to populate the static data in these tables. This script could be appended to the end of the table script, or made it's own script, or even made one script per table, a good idea if you have hundreds or thousands of rows to load. (Some folks make a csv file and then issue a BULK INSERT on it, but I'd avoid that is it just gives you two files and a complex process [configuring drive mappings on deployment] to manage.)
The key thing to remember is that data (as stored in databases) can and will change over time. Rarely (if ever!) will you have the luxury of deleting your Production database and replacing it with a fresh, shiny, new one devoid of all that crufty data from the past umpteen years. Databases are all about changes over time, and that's where scripts come into their own. You start with the scripts to create the database, and then over time you add scripts that modify the database as changes come along -- and this applies to your static data (of any type) as well.
(Ultimately, my methodology is analogous to accounting: you have accounts, and as changes come in you adjust the accounts with journal entries. If you find you made a mistake, you never go back and modify your entries, you just make a subsequent entries to reverse and fix them. It's only an analogy, but the logic is sound.)

The solution I use is to have create and change scripts in source control, coupled with version information stored in the database.
Then, I have an install wizard that can detect whether it needs to create or update the db - the update process is managed by picking appropriate scripts based on the stored version information in the database.

See this thread's answer. Static data from your first two points should be in source control, IMHO.
Edit: *new
all-in-one or a separate script? it does not really matter as long as you (dev team) agree with your deployment team. I prefer to separate files, but I still can always create all-in-one.sql from those in the proper order [Logins, Roles, Users; Tables; Views; Stored Procedures; UDFs; Static Data; (Audit Tables, Audit Triggers)]
how do you make sure they execute it: well, make it another step in your application/database deployment documentation. If you roll out application which really needs specific (new) static data in the database, then you might want to perform a DB version check in your application. and you update the DB_VERSION to your new release number as part of that script. Then your application on a start-up should check it and report an error if the new DB version is required.
dev and non-dev static data: I have never seen this case actually. More often there is real static data, which you might call "dev", which is major configuration, ISO static data etc. The other type is default lookup data, which is there for users to start with, but they might add more. The mechanism to INSERT these data might be different, because you need to ensure you do not destoy (power-)user-created data.