So I'm trying to figure out how much capabilities comes with Intersystems to send data to an XDS repository. Specifically with using the basic Ensemble package (NO HSF) Assume it's not the one Intersystems delivers, but an external XDS repository.
Is there a built-in way to send a large blob and wrap the ebRim around that blob?
As you can see at http://www.intersystemsbenelux.com/media/media_manager/pdf/1398.pdf, Ensemble does not natively support ebRIM, but it does support XML and XML schemas.
Maybe you could assemble an XML and use that to wrap your blob content.
You can send that over whatever protocol your XDS system provides (xDBC, SOAP, file system etc). Take a look at the items listed on sections "Ensemble Interoperability" and "Ensemble Adapter and Gateway Guides" of http://docs.intersystems.com/ens20122/csp/docbook/DocBook.UI.Page.cls for a full list of connectivity options.
Regards,
There is healthshare foundation product which has XDS connectivity
See this good answer on google groups https://groups.google.com/forum/m/?fromgroups#!topic/Ensemble-in-Healthcare/h7R300H68KQ
Or healthshare part of their website
HSF (HealthShare Foundation) XDS.b connectivity for query and retrieve and also the Provide and Register Operation.
Ok, so I re-read your question and have an answer for you. I think what you are trying to say is that you have Ensemble, not HSF, and you still want to be able to send documents (XDS provide and Register).
I did some testing with the Open Source Integration mirth and stumbled across an example channel of theirs, and it is doing a provide and register with straight up SOAP calls to the end point.
Basically, build the required soap envelope accordingly, then send a PDF or document to the repository using MTOM.
This is what makes HealthShare its money, encapsulating all that manual construction of objects that need to be sent to endpoints.
Anyway, a screenshot of the Mirth channel destination make give you an understanding:
http://www.integrationrequired.com/wp-content/uploads/2013/02/Capture.PNG
Related
I am trying to see if an external API can be consumed from Microstrategy. I am new to this and so far I have seen a connector on Microstrategy that allows you to bring data from an URL, but when things get more complex like passing a specific header parameter, then the connector is not useful.
Also going through the documentation I have seen they have internal APIs that any external application can consume to create reports outside of Microstrategy or to join data hosted on Microstrategy.
Their documentation for internal APIs is this one, but I am sure the other way around is possible, I just need a direction or an example to understand.
https://www.microstrategy.com/en/support/support-videos/how-to-use-the-rest-api-in-library
You can use XQuery for this. You can look there;
https://www2.microstrategy.com/producthelp/Current/AdvancedReportingGuide/WebHelp/Lang_1033/Content/Using_XQuery_to_retrieve_data_from_a_web_service.htm#freeform_sql_4027597040_1133899
https://community.microstrategy.com/s/article/How-to-Create-a-Report-That-Dynamically-Retrieves-Data-From-a-Parameterized-Web-Service?language=en_US
I've samples for that, we can talk about that.
You can try the external data function provided by rest api.
The Push Data API, which belongs to the Dataset API family, lets you
make external data easily available for analysis in MicroStrategy. You
use REST APIs to create and modify datasets using external data
uploaded directly to the Intelligence Server.
By providing a simpler, quicker way to get data out and add data back
in, the Push Data API makes it easier to use MicroStrategy as a
high-performance data storage and retrieval mechanism and supports
predictive workflow by machine learning, artificial intelligence, and
data scientist teams. The ability to make external data easily
available extends MicroStrategy's reach to new and complex data
sources where code, rather than end-users, manages the data
modeling/mapping flow. The Push Data API supports close integration
with the ecosystem of third-party ETL tools because it allows them to
push data directly into MicroStrategy while allowing the most optimal
utilization of MicroStrategy's cube capabilities. The Push Data API
provides these tools, whether they are analyst or IT-oriented, with
the option to create and update datasets on the MicroStrategy
Intelligence Server without requiring an intermediate step of pushing
the data into a warehouse.
You can first make sure the data is ready in your local environment and then push it to the MSTR server as the instruction.
https://www2.microstrategy.com/producthelp/Current/RESTSDK/Content/topics/REST_API/REST_API_PushDataAPI_MakingExternalDataAvailable.htm
I am new to BizTalk. I got a requirement as below.
Requirement is below:-
Source: Oracle (table). I created a generated schema in BizTalk.
Target: Webservice which receives "object array" (Table of source records from BizTalk) as an input.
Source and Target systems have same structure. Hence no mapping should be implemented. Logic should be in pipelines or orchestration.
Need info on below two topics:
How to incorporate the logic in pipeline or orchestration to map data from source schema to target WS schema.
This question was posed (now deleted) on the other big BizTalk forum. So I'll share my answer here.
What you're asking is simply not possible. It doesn't matter that the source and destination are logically the same. They are represented by two different schemas in BizTalk. There is no way around this except by developing the Web Service to accept the WCF Oracle message directly.
Because of that, you must transform from the source to the destination. Maps are how that is done. While there are technically other ways, they are harder to write, bug prone and would likely offer a less desirable performance profile.
A ban on Maps is just counter-productive and as a long time BizTalk Developer I could not accept a project with such a requirement.
It's not very clear what you are asking for to be honest. Your requirement states that no mapping is required, but then you go on to ask how to incorporate mapping in pipeline or orchestrations.
A standard approach to delivering this would be;
Setup your input process from Oracle by using "Consume Adapter
Service" from visual studio's "add generated item". Use the oracle
binding, setup connection properties for typed polling along with
your query (see here for an example on MS SQL) change to a
service contract type (for inbound operations) and you'll get a set
of schemas representing your dataset, and a binding for your type
receive port poller.
Use "Consume WCF Service" to point to your "sending" web service and
you'll get the schemas, binding and a helpful orchestration with
port types add to your project
Create a simple map mapping your inbound oracle recordset schema to
your web service schema - this should be pretty straight forward if
they are identical, although I suspect you'll have to deal with
multiple sets of data - depends on your data.
Complete by wiring together your orchestration.
I appreciate this is a high level view of what you need to do, but there are plenty of example you can google to get you started. Hope that helps.
I saw this previous post but I have not been able to adapt the answer to get my code to work.
I am trying to filter on the term bruins and need to reference cacert.pem since for authentication on my Windows machine. Lastly, I have written a function to parse each response (my.function) and need to include this as well.
postForm("https://stream.twitter.com/1/statuses/sample.json",
userpwd="user:pass",
cainfo = "cacert.pem",
a = "bruins",
write=my.function)
I am looking to stay completely within R and unfortunately need to use Windows.
Simply, how can I include the search term(s) that I want such that the response is filtered?
Thanks in advance.
Alright, so I've looked at what you're doing, and some of what you're working on may be helped by examining the Twitter API methods, although it can be difficult to figure out how to translate some of the examples into R (via the RCurl Package).
What you're currently trying is very close to what you need to do, you simply need to change two things.
First of all, you're querying the url for the random sample of statuses. This url returns a random sample of roughly 1% of all tweets.
If you're interested in collecting only tweets about specific keywords, you want to use the filter API url: "https://stream.twitter.com/1/statuses/filter.json"
After changing that, you simply need to change your parameter from "a" to "postfields", and the parameter you'd be passing would look like: "track=bruins"
Finally, you should use the getURL function, to open a continuous stream, so all tweets with your keywords can be collected, rather than using the postForm command (which I believe is intended for HTML forms).
so your final function call should look like the following:
getURL("https://stream.twitter.com/1/statuses/filter.json",
userpwd="Username:Password",
cainfo = "cacert.pem",
write=my.function,
postfields="track=bruins")
For manipulating twitter, use the twitteR package.
library(twitteR)
searchTwitter("bruins")
You can include other parameters (like cainfo) in the call to searchTwitter, and they should get passed getForm underneath.
I don't think the Streaming API is currently included in twitteR - the search api is different (it's backward looking, whereas streaming is "current looking").
From my understanding, streaming is quite different to how lots of APIs work typically work; rather than pulling data from a web service and having a defined object returned, you're setting up a "pipe" for Twitter to push data to you and you then listen for that response.
You also need to worry about OAuth I think (which twitteR does deal with).
Is there any reason that you want to keep in R? I've used python successfully with the Streaming API and a package called tweepy to write data to a MySQL database and then use R to query and analyse the data.
Last time I checked, twitteR did not talk to the streaming API. Moreover, as far as I know, very few publicly-available Twitter Streaming API connection libraries in any language honor Twitter's recommendations on reconnecting when Streaming disconnects / throws an error.
My recommendation is to access Streaming via a library that's actively maintained, write the re-connection protocol yourself if you have to, and persist the data into a database that handles JSON natively. I'm about to embark on a project of this nature and will be writing the collector in Perl, doing my own re-connect logic and persisting into either PostgreSQL or MongoDB. Most likely it will be MongoDB; PostgreSQL doesn't get native JSON till 9.2.
Late to the game, I know, but you'll want to use the "streamR" package for access to Twitter's streaming API.
I am currently working on system that generated product recommendations like those on Amazon : "People who bought this also bought this.."
Current Scenario:
Extract the Google Analytics data of the client and insert it in database.
On the website of the client, on load of product page the API call is made to get the recommendations of the product being viewed.
When API receives the product ID as request it looks in the database and retrieves (using association rules) the recommended product IDs and sends them as response.
The list of these product Ids will be processed to get the product details(image,price..) at the client end and displayed on website.
Currently I am using PHP and MYSQL with gapi package and REST api
storage on AMAZON EC2 .
My Question is:
Now, if I have to choose amongst the following, which will be the best choice to implement the above mentioned concept.
PHP with SimpleDB or BIGQuery.
R language with BIGQuery.
RHIPE-(R and hadoop ) with SimpleDB.
Apache Mahout.
Plese help!
This isn't so easy to answer, because the constraints are fairly specialized.
The following considerations can be made, though:
BIGQuery is not yet public. Thus, with a small usage base, even if you are in the preview population, it will be harder to get advice on improvement.
Each of your answers asked about a modeling system & a storage system. Apache Mahout is not a storage mechanism, so it won't necessarily work on its own. I used to believe that its machine learning implementations were a a pastiche of a few Google Summer of Code, but I've updated that view on the suggestion of a commenter. It still looks like it has rather uneven and spotty coverage of different algorithms, and it's not particularly clear how the components are supported or maintained. I encourage an evangelist for Mahout to address this.
As a result, this eliminates the 1st, 2nd, and 4th options.
What I don't quite get is the need for a real-time server to utilize Hadoop and RHIPE. That should be done in your batch processing for developing the recommendation models, not in real-time. I suppose you could use RHIPE as a simple one-stop front end for firing off queries.
I'd recommend using RApache instead of RHIPE, because you can get your packages and models pre-loaded. I see no advantage to using Hadoop in the front end, but it would be a very natural back end system for the model fitting.
(Update 1) Other interface options include RServe (http://www.rforge.net/Rserve/) and possibly RStudio in server mode. There are R/PHP interfaces (see comments below), but I suspect it would be better to access R through HTTP or TCP/IP.
(Update 2) Addressing the whole process, the basic idea I see is that you could query the data from PHP and pass to R or, if you wish to query from within R, look at the link in the comments (to the OmegaHat tools) or post a new question about R & SimpleDB - I'm sure someone else on SO would be able to give better insight on this particular connection. RApache would let you instantiate many R processes already prepared with packages loaded and data in RAM; thus you would only need to pass whatever data needs to be used for prediction. If your new data is a small vector then RApache should be fine, and it seems this is correct for the data being processed in real-time.
If you want a real-time API for recommendations based on data in a database, Apache Mahout does this directly. You want to use ReloadFromJDBCDataModel, put on top a GenericItemBasedRecommender, and use the servlet-based wrapper in the examples module. It's probably a day or two of work to get familiar with the code and customize it to your needs, but it's pretty simple.
When you get past about 100M data points you would need to look at distributing the computation Hadoop. That's a fair bit more complex. Mahout has a distributed recommender too which you can customize.
I’m a complete newbie at BizTalk and I need to create a BizTalk 2006 application which broadcasts messages in a specific way. I’m not asking for a complete solution, but for advise and guidelines, which capabilities of BizTalk I should use.
There’s a message source, for simplicity, say, a directory where the user adds files to publish them. There are several subscribers, each having a directory to receive published files. The number of subscribers can vary in the course of exploitation of the program. There are also some rules which determine if a particular subscriber needs to receive a particular file, based on the filename. For example, each subscriber has a pattern or mask of filename which files they receives must match. Those rules (for example, patterns) can change in time as well.
I don’t know how to do this. Create a set of send ports at runtime, each for each destination? Is it possible? Use one port changing its binding? Would it work correctly with concurrent sendings? Are there other ways?
EDIT
I realized my question may be to obscure and general to prefer one answer over another to accept. So I just upvoted them.
You could look at using dynamic send ports to achieve this - if your subscribers are truly dynamic. This introduces a bit of complexity since you'll need to use an orchestration to configure the send port's properties based on your rules.
If you can, try and remove the complexity. If you know that you don't need to be truly dynamic when adding subscribers (i.e. a subscriber and it's rules can be configured one time only) and you have a manageable number of subscribers then I would suggest configuring each subscriber using it's own send port and use a filter to create subscriptions based on message context properties. The beauty of this approach is that you don't need to create and deploy an orchestration and this becomes a highly performant and scalable solution.
If the changes to the destination are going to be frequent, you are right in seeking a more dynamic solution. One nice solution is using dynamic send ports and the Business Rules Engine. You create rule set for the messages you are receving. This could be based on a destination property or customer ID in the message. Using these facts, the rules engine can return a bunch of information like file mask, server name, ip address of deleiver server, etc. You can thenuse this information to configure the dynamic send in the orchestration. The real nice thing here is that you can update the rule set in the rules engine without redeploying the whole solution. As a newb, these are some advanced concepts, but not as diificult as you may think.
For a simpler solution, you might want to look at setting the FILE Send adapters properties via it's Propery Schema (ie. File name, Directory, etc.). You could pull these values from a database with a helper class inside an expresison shape. On each message ogig out, use the property shcema to set where the message will be sent and named. This way, you just update the database as things change.
Good Luck!