Keeping and managing a history on data - orientdb

I am considering the possibility of keeping history of all the data changes on a OrientDB database. This history shall be explorable just like the normal data. Like: I shall be able to query all the changes that a user have ever done to his profile.
I considered some solution like suggested here to create history classes for each vertex class and to create a history record for each update (vertex version increase) in that class whenever a vertex changes.
Can this be done directly inside DB using some kind of trigger like what Oracle has?
Even if that served for normal data of vertex what about edges? how could I preserve them in history? and between vertices?
I there a more straight forward way to do this in OrientDB?

I would suggest to keep the changes and the history in some kind of event store. This can be a sequence of events, each is immutable, records will be appended only.
This could look like
VERTEX_CREATED(id: 1337, time: 1336624823)
VERTEX_CHANGED(field: foo, before: A, after: B, time: 133676328)
...
This makes it possible to replay the history from any point you want, you can skip entries to supress errors which occured and so on.
If you store such records in a table or in a graph is not relevant. Inside a graph, this could be nodes, where each node is connected with the event before and after itself, like a linked list. In a table this would be only rows.
If you want to learn more about this approach, I can suggest you Event Sourcing by Martin Fowler.

Related

Cannot repopulate ElectrodeGroup datajoint table

I'm a researcher in Loren Frank's lab at UCSF using datajoint and files in the nwb format. I made some changes to our code for defining entries in our ElectrodeGroup table, and was hoping to test those by deleting an entry in the table and regenerating it with the new code. I was able to delete the entry, but cannot repopulate it. In particular, when I run ElectrodeGroup.populate() or ElectrodeGroup.populate({"nwb_file_name": my_file_name}), no changes are made to the table. I confirmed that the electrode group I deleted and am trying to regenerate is defined in the original nwb file. I am seeking input on why the populate command seems to not be working here. Thanks in advance for any help!
This user also contacted our team through another channel. Sharing the solution below for future users, in reference to this schema. In short, the populate process is reserved for unique upstream primary keys.
Since the ElectrodeGroup's only upstream table dependency is Session, the make method will only be called if there are no electrode groups for that session. This is because from the perspective of DataJoint, the only 'guaranteed' knowledge about what should exist for this table is defined solely by the presence/absence of related upstream records. Since the 'new' primary 'electrode_group_name' attribute is defined by the ElectrodeGroup table itself, DataJoint doesn't know how many copies will be created by make, and so simply invokes make 1 time per Session, expecting the single make invocation to fully define all possible electrode_group_name values the table will use. If there is one value for that session, no work needs to be done, so no make() invocation occurs.
There are a couple possible solutions:
Model the electrode group explicitly, with a table defines the existence of an electrode group (e.g., ElectrodeGroupConfiguration). This ElectrodeGroup would then inherit primary keys from both Session and ElectrodeGroupConfiguration. The ElectrodeGroup make function would be adjusted to load that unique keys across upstream tables.
Adjust the make function to handle the partial insert/update case, and call the make function directly with the desired primary key when these kinds of 'abnormal' updates need to occur.
Method #1 is 'cleanest' w/r/t to the DataJoint data model (explicitly modeled data dependencies using make/populate), whereas #2 is slightly 'escaping' the DataJoint data model in a controlled way to achieve a desired schema/data result.

How doest Trello store generated actions from updates to other documents (boards, cards) in MongoDB without atomic transactions?

I'm developing a single page web app that will use a NoSQL Document Database (like MongoDB) and I want to generate events when I make a change to my entities.
Since most of these databases support transactions only on a document level (MongoDB just added ASIC support) there is no good way to store changes in one document and then store events from those changes to other documents.
Let's say for example that I have a collection 'Events' and a collection 'Cards' like Trello does. When I make a change to the description of a card from the 'Cards' collection, an event 'CardDescriptionChanged' should be generated.
The problem is that if there is a crash or some error between saving the changes to the 'Cards' collection and adding the event in the 'Events' collection this event will not be persisted and I don't want that.
I've done some research on this issue and most people would suggest that one of several approaches can be used:
Do not use MongoDB, use SQL database instead (I don't want that)
Use Event Sourcing. (This introduces complexity and I want to clear older events at some point, so I don't want to keep all events stored. I now that I can use snapshots and delete older events from the snapshot point, but there is a complexity in this solution)
Since errors of this nature probably won't happen too often, just ignore them and risk having events that won't be saved (I don't want that too)
Use an event/command/action processor. Store commands/action like 'ChangeCardDescription' and use a Processor that will process them and update the entities.
I have considered option 4, but a couple of question occurs:
How do I manage concurrency?
I can queue all commands for the same entity (like a card or a board) and make sure that they are processed sequentially, while events for different entities (different cards) can be processed in parallel. Then I can use processed commands as events. One problem here is that changes to an entity may generate several events that may not correspond to a single command. I will have to break down to very fine-grained commands all user actions so I can then translate them to events.
Error reporting and error handling.
If this process is asynchronous, I have to manage error reporting to the client. And also I have to remove or mark commands that failed.
I still have the problem with marking the commands as processed, as there are no transactions. I know I have to make processing of commands idempotent to resolve this problem.
Since Trello used MongoDB and generates actions ('DeleteCardAction', 'CreateCardAction') with changes to entities (Cards, Boards..) I was wondering how do they solve this problem?
Create a new collection called FutureUpdates. Write planned updates to the FutureUpdates collection with a single document defining the changes you plan to make to cards and the events you plan to generate. This insert will be atomic.
Now take a [ChangeStream][1] of the FutureUpdates collection this will give you the stream of updates you need to make. Take each doc from the change stream and apply the updates. Finally, update the doc in FutureUpdates to mark it as complete. Again this update will be atomic.
When you apply the updates to Events and Cards make sure to include the objectID of the doc used to create the update in FutureUpdates.
Now if the program crashes after inserting the update in FutureUpdates you can check the Events and Cards collections for the existence of records containing the objectID of the update. If they are not present then you can reapply the missing updates.
If the updates have been applied but the FutureUpdate doc is not marked as complete we can update that during recovery to complete the process.
Effectively you are continuously atomically updating a doc for each change in FutureUpdates to track progress. Once an update is complete you can archive the old docs or just delete them.

Should I update read model on each event

I have Customer read model that needs to be updated after NewOrderEvent.
One thing i want to understand, should i update my read model on every event. Or i need to replay all events and replace read model.
What im doing now is:
Saving NewOrderEvent
Getting or creating Customer read model
Invoking Customer.ApplyEvent(NewOrderEvent) that changes Customer state.
Saving Customer read model
Am i missing something?
Usually yes, you want to update the read model every time you have an event. But, it's just a simple CRUD operation, a db update. The replaying of events is done when you want to (re)generate a new read model, because you could have millions of events and could be a very long running operation.
Btw, the apply stuff should be reserved for command model only, in order to avoid confusion. You apply events to a domain aggregate root (entity), but you use an event as the source of data for read model updates.
Looks good to me. You may decide to replay the stream of events in order to recreate the read model only if you introducing something new to it.
Some people rebuild read models whenever the schema changes, but in many cases you can use migrations for that. Really depends on your application.

Visio 2013: How to trigger a change in databinding of all shapes

I have a nice process overview for our ordering process in Visio. I have an external data source (SQL Server), which works fine. Every record in my data source represents one ordering process. Currently all my shapes of the process are linked to the first record of the data source.
Now I want to add a dynamic behavior. What I want to achieve is this:
A user provides the order reference in a textbox (order reference is a column in the data source)
Afterwards the user clicks a button
After the button click, the process is updated and all shapes are now linked to the external data source record, that matches the provided order reference
So in short: the user should be able to select which process that needs to be visualized.
I assume that this is common functionality, but I don't see how I can deal with this requirement. I've searched already some days on this issue, but without any success.
Can you help me with this issue?
Thanks a lot!
Problem solved :-)
Some old school VBA was required. Using the DataRecordSet object did the trick. It contains a method GetDataRowIDs that you can use to query the external dataset. Once you have the record to visualize, it's just a matter of dynamically updating the shapes with the correct record. Use macro recording to see how to do this.
MSDN: http://msdn.microsoft.com/en-us/library/office/ms195694(v=office.12).aspx

Last Updated Date: Antipattern?

I keep seeing questions floating through that make reference to a column in a database table named something like DateLastUpdated. I don't get it.
The only companion field I've ever seen is LastUpdateUserId or such. There's never an indicator about why the update took place; or even what the update was.
On top of that, this field is sometimes written from within a trigger, where even less context is available.
It certainly doesn't even come close to being an audit trail; so that can't be the justification. And if there is and audit trail somewhere in a log or whatever, this field would be redundant.
What am I missing? Why is this pattern so popular?
Such a field can be used to detect whether there are conflicting edits made by different processes. When you retrieve a record from the database, you get the previous DateLastUpdated field. After making changes to other fields, you submit the record back to the database layer. The database layer checks that the DateLastUpdated you submit matches the one still in the database. If it matches, then the update is performed (and DateLastUpdated is updated to the current time). However, if it does not match, then some other process has changed the record in the meantime and the current update can be aborted.
It depends on the exact circumstance, but a timestamp like that can be very useful for autogenerated data - you can figure out if something needs to be recalculated if a depedency has changed later on (this is how build systems calculate which files need to be recompiled).
Also, many websites will have data marking "Last changed" on a page, particularly news sites that may edit content. The exact reason isn't necessary (and there likely exist backups in case an audit trail is really necessary), but this data needs to be visible to the end user.
These sorts of things are typically used for business applications where user action is required to initiate the update. Typically, there will be some kind of business app (eg a CRM desktop application) and for most updates there tends to be only one way of making the update.
If you're looking at address data, that was done through the "Maintain Address" screen, etc.
Such database auditing is there to augment business-level auditing, not to replace it. Call centres will sometimes (or always in the case of financial services providers in Australia, as one example) record phone calls. That's part of the audit trail too but doesn't tend to be part of the IT solution as far as the desktop application (and related infrastructure) goes, although that is by no means a hard and fast rule.
Call centre staff will also typically have some sort of "Notes" or "Log" functionality where they can type freeform text as to why the customer called and what action was taken so the next operator can pick up where they left off when the customer rings back.
Triggers will often be used to record exactly what was changed (eg writing the old record to an audit table). The purpose of all this is that with all the information (the notes, recorded call, database audit trail and logs) the previous state of the data can be reconstructed as can the resulting action. This may be to find/resolve bugs in the system or simply as a conflict resolution process with the customer.
It is certainly popular - rails for example has a shorthand for it, as well as a creation timestamp (:timestamps).
At the application level it's very useful, as the same pattern is very common in views - look at the questions here for example (answered 56 secs ago, etc).
It can also be used retrospectively in reporting to generate stats (e.g. what is the growth curve of the number of records in the DB).
there are a couple of scenarios
Let's say you have an address table for your customers
you have your CRM app, the customer calls that his address has changed a month ago, with the LastUpdate column you can see that this row for this customer hasn't been touched in 4 months
usually you use triggers to populate a history table so that you can see all the other history, if you see that the creationdate and updated date are the same there is no point hitting the history table since you won't find anything
you calculate indexes (stock market), you can easily see that it was recalculated just by looking at this column
there are 2 DB servers, by comparing the date column you can find out if all the changes have been replicated or not etc etc ect
This is also very useful if you have to send feeds out to clients that are delta feeds, that is only the records that have been changed or inserted since the data of the last feed are sent.