How can I create the maintainability index with cql?
Does the NDepend calculate this number?
Thanks!
Alejandra
Don't know about CQL. SD's C# Metrics tool calculate the SEI Maintainability index directly. See
C# Metrics Tool.
Related
I have very simple queries around Data Fusion and the ETL transformation capabilities:
How do you sort a file in data fusion using a particular column/columns? Couldn't find any plugin or any directive in wrangler.
How do you perform a cumulative aggregation?
Not sure if I completely understood the use case, but I'll answer to the best of my understanding and knowledge.
If you're looking to sort records from an input set, then hopefully the TopN plugin (which can be deployed from the Hub) will be useful to you. You could try to use it in conjunction with other plugins (in case you wish to output records to a file for example). In regards to Wrangler - I also couldn't find that Wrangler has a sorting operation available currently (see cheatsheet here, ‘develop’ branch).
As Sakshi also suggested, you could use the Group by plugin in the Analytics section of Data Fusion UI to perform aggregations.
For reference, Cloud Data Fusion plugins list is available here.
If this is not what you are looking for, then it’ll be helpful if you could share more about your use case and maybe provide an example of the input vs output.
is there any way to run Tinkerpop Gremlin 3.1 traversals in OrientDB?
I've noticed that currently the DBMS supports the previous version (2.x) of the Tinkerpop traversal language which, for example, only allows to directly filter edges by label, but not vertices :( .
I was quite satisfied with gremlin-scala and orientDB-gremlin but I found that not all my queries where efficiently executed (some indexes were ignored).
Is there any other way?
Thanks in advance :)
Orientdb-gremlin is indeed the only available driver, and while it works pretty well for base cases there's some work left for index usage. If you report your cases in a github issue we can have a look. Best is obviously if you submit a PR :)
This article offered me a huge amount of information:
Implement Lucene on Existing .NET / SQL Server stack with multiple webservers
I'd like to follow on from this by asking about the notion of implementing a Lucene Directory that would persist the indexes to the database (in my case SQL Server) - if anyone has a SWAG on effort that would be helpful.
I can see that the Java realm has this (e.g. Compass), and I'm really hoping the Stackoverflow folks might have considered this to? Any feedback would be appreciated.
My rookie thinking is that persisting indexes to the DB would be a way to solve for the 'distribution' problem. So instead of implementing messaging (not possible for my software because of deployment restrictions), or scheduling (would be ok'ish - product folks always get jumpy in making decisions about how 'current' indexed data has to be), the IndexReader reopen() would efficiently update the index snapshot on whichever server node.
Does this work if DB concurrency/load is not the heart of the problem being solved? - our use is focused around facilitating different data analysis on fields which in turns facilitates different forms of matching.
Our deployment architecture/restrictions do not really allow us to insist on dedicated servers ala SOLR, so this notion of distribution has been discounted by us.
How much index changes do you await? When do you want to read in the index? (On application startup?) Putting the index into the database and "downloading" it on index creation might consume too much resources.
Not sure about your deployment restrictions, but can you have a shared file space for your machines (e.g. SMB/NFS share or similar, or even a SAN-based solution)?
I would be a bit afraid of performance issues with the indexes in the db. Have a look at Elasticsearch. It's the successor of compass. It requires Java, but has a very neat REST interface for your .NET solution. Elasticsearch supports distribution and replication between several nodes. You can run it on the webserver nodes.
This solution will kill performance of the index, since it has to retrieve it from the DB.
I would highly recommend moving to a newer/better alternative, that is Solr (using Solr.NET for example) or ElasticSearch (using NEST)
Solr is a high level interface/manager for Lucene indexes, with a simplified configuration, clustering, replication, etc. solved for you. The nice thing is that if you have some exp. with Lucene, this will not be such a big step
ElasticSearch is a different approach but it's not hard to learn.
I'm looking for a little assistance in Scala similar to that provided by pyTables. PyTables is a package for managing hierarchical datasets and designed to efficiently and easily cope with extremely large amounts of data.
Any suggestions?
I had a quick look at pyTables, and I don't think there's anything remotely like it in Scalaland (or indeed Javaland), but we have a few of the ingredients necessary to make it a possibility if you want to invest the time:
scala.Dynamic to do idiomatic selection on data-driven structures
A bunch of graph databases to provide the underlying navigational persistence substrate (I've had acceptable results from OrientDB, which has a better license than most)
PyTables is a python implementation of HDF5 with some added niceties to let you work on it in a pythonic way, and get good indexing support. I'm not sure if there's a package implemented in a similar way in Scala, but you can use the same HFD5 based hierarchical data storageusing the HDF5 implementation in Java: HDF Java
I'm working my way through a postgres query plan for the first time.
I'm having some trouble because I don't seem to be able to find any documentation that describes what each of the plan nodes are. In many cases, the name provides me with a reasonable guess, but in several the name of the plan node is too generic for me to have confidence in it.
Where can I find a list of types of plan nodes, with descriptions of each?
Chapter "56.1. Row Estimation Examples" explaines a lot, take a look.
Adding to Frank's answer, you might also want to peek at:
http://explain.depesz.com/
It reformats the plans in a more readable manner.