We have a Cloudant database on Bluemix that contains a large number of documents that are answer units built by the Document Conversion service. These answer units are used to populate a Solr Retrieve and Rank collection for our application. The Cloudant database serves as our system of record for the answer units.
For reasons that are unimportant, our Cloudant database is no longer valid. What we need is a way to download everything from the Solr collection and re-create the Cloudant database. Can anyone tell me a way to do that?
I'm not aware of any automated way to do this.
You'll need to fetch all your documents from Solr (and assuming you have a lot of them, do this in a paginated way - there are some examples of how to do this in the Solr doc) and add them into Cloudant.
Note that you'll only be able to do this for the fields that you have set to be stored in your schema. If there are important fields that you need in Cloudant that you haven't got stored in Solr, then you might be stuck. :(
You can replicate one Cloudant database to another which will create you an exact replica.
Another technique is to use a tool such as couchbackup which takes a copy of your database's documents (ignoring any deletions) and allows you to save the data in a text file. You can then use the couchrestore tool to upload the data file to a new database.
See this blog for more details.
Related
We have an ad search website and all the searches are being done through entity framework directly querying the sql server database.
It was working very well when the database had around 1000 ads, but now it is reaching 300k and lots of users searching. The searches now are very slow (using raw sql didn't help much) and I was instructed to consider Elasticsearch.
I've been some tutorials and I get the idea of how it works now, but what I don't know is:
Should I stop using sql server to store the ads and start using Elasticsearch instead? What about all the other related data? Is Elasticsearch an alternative to sql server?
Each Ad has some related data stored in different tables, how would I load it to Elasticsearch? As a single json element?
I read a lot of "billions of data" handled by Elasticsearch, so I don't think I would have performance problems with 300k rows in it, correct?
Would anybody explain me better these questions?
1- You could still use it; you don't want to search over the complete database, rigth? Just over the ads. It works with a no-sql format, so it is very scalable. It also works with json's so you have an easy form to access it.
2- When indexing data, you should try to add the complete necessary data in the same document(sql row), which is a single json, but in a limited way. Storage is cheap, but computing time isn't.
To index your data, you could either use filebeat, a program a bit similar to logstash, or create your own solution like, making a program that reads data from your db, and then passes it to elasticsearch in bulks.
3- Correct, 300k rows is a small quantity, but it also depends on the memory from where you are hosting elasticsearch.
Hope this helps.
I have queries/views/design docs in cloudant. I want to move them to another database. Is there any way?
Cloudant/CouchDB replication will copy all of the documents (including design documents) to the target databases, as long as the user being used to authenticate against the target database has 'admin' access - because you need admin access to write a design document.
There's no built-in way with Cloudant. If you want to write a NodeJS program, it's pretty easy. Here's a gist that deletes all documents except design docs. It could quickly be modified to copy the design docs to a different database. https://gist.github.com/rajrsingh/6044d58e2ae743d7ec5b
Coming from a RDBMS background and trying to wrap my head around ElasticSearch data storage patterns...
Currently in SQL Server, we have a star schema data mart, RecordData. Rows are organized by user ID, geographic location that pertains to the rest of the searchable record, title and description (which are free text search fields).
I would like to move this over to ElasticSearch, and have read about creating a separate index per user. If I understand this correctly, with this suggestion, I would be creating a RecordData type in each user index, correct? What is a recommended naming convention for user indices that will be simple for Kibana analysis?
One issue I have with this recommendation is, how would you organize multiple web applications on the ES server? You wouldn't want to have all those user indices all over the place?
Is it so bad to have one index per application, and type per SQL Server table?
Since in SQL Server, we have other tables for user configuration, based on user ID's, I take it that I could then create new ES types in user indices for configuration. Is this a recommended pattern? I would rather not have two data base systems for this web application.
Suggestions welcome, thank you.
I went through the same thing, and there are a few things to take into account.
Data Modeling
You say you use a star schema today. Elasticsearch is typically appropriate for denormalized data where the totality of the information resides in each document unlike with a star schema. If you can live with denormalized, that is fine but I assume that since you already have star schema, denormalized data is not an option because you don't want to go and update millions of documents each time the location name change for example(if i understand the use case). At least in my use case that wasn't an option.
What are Elasticsearch options for normalized data?
This leads us to think of how to put star schema like data in a system like Elasticsearch. There are a few options in the documentation, the main ones i focused were
Nested Objects - more details at https://www.elastic.co/guide/en/elasticsearch/guide/current/nested-objects.html . In nested objects the entire information is kept in a single document, meaning one location and its related users would be in a single document. That may make it not optimal becasue the document will be huge and again, a change in the location name will require to update the entire document. So this is better but still not optimal.
Parent - Child Relationship - more details at https://www.elastic.co/guide/en/elasticsearch/guide/current/parent-child.html . In this case the location and the User records would be kepts in separate indices similarly to a relational database. This seems to be the right modeling for what we need. The only major issue with this option is the fact that Kibana 4 does not provide ways to manipulate/aggregate documents based on parent/child relationship as of this writing. So if you main driver for using Elasticsearch is Kibana(this was mine), that kind of eliminates the option. If you want to benefit from the elasticsearch speed as an engine this seems to be the desired option for your use case.
In my opinion once you got right the data modeling all of your questions will be easier to answer.
Regarding the organization of the servers themselves, the way we organize that is by having a separate cluster of 3 elasticsearch nodes behind a Load Balancer(all of that is hosted on a cloud) and then have all your Web Applications connect to that cluster using the Elasticsearch API.
Hope that helps.
Is solr just for searching ie it's not for 'updating' or 'inserting' data?
My site is currently MySQL based, and on looking at SOLR as an alt option, I see you make your queries through http requests.
My first thought was - how do you stop someone from making a query that updates or inserts data?
Obviously, I'm not understanding SOLR, hence my question here.
Cheers
Solr mainly is for Full Text search, and rather should not be used as a Persistent store.
Solr stores its data in the File store and does not provide the features of Relational database (ACID or Nested Entities etc )
Usually, the model followed is use Relationship database for you data management.
Replicate the data into Solr for Full Text search.
You can always control the Insert/Update access for Solr by securing the urls.
I have a Solr database snapshot. The database is an archive of published blog posts (plus a bunch of metadata for each post). The snapshot is tens of thousands of posts.
I want to run some machine learning algorithms and topic modeling on the posts. So I don't need the database per se, I just want to get the raw text of the posts and the metadata in some simple form. Can anyone tell me how to open or extract that info without actually installing Solr?
I suppose you have the Solr Index when you mean the Solr database snapshot.
Solr index is basically a lucene index and you can use the Lucene apis to just read the index and extract data from the fields.
This would not need Solr to be installed.