My application requires some kind of data backup and some kind of data exchange between users, so what I want to achieve is the ability to export an entity but not the entire database.
I have found some help but for the full database, like this post:
Backup core data locally, and restore from backup - Swift
This applies to the entire database.
I tried to export a JSON file, this might work except that the entity I'm trying to export contains images as binary data.
So I'm stuck.
Any help exporting not the full database but just one entity or how to write a JSON that includes binary data.
Take a look at protobuf. Apple has an official swift lib for it
https://github.com/apple/swift-protobuf
Protobuf is an alternate encoding to JSON that has direct support for serializing binary data. There are client libraries for any language you might need to read the data in, or command-line tools if you want to examine the files manually.
Related
I have millions of documents in different collections in my database. I need to export them to a csv onto my local storage when I specify the collection name.
I tried mlcp export but didn't work. We cannot use corb for this because of some issues.
I want the csv to be in such a format that if I try a mlcp import then I should be able to restore all docs just the way they were.
My first thought would be to use MLCP archive feature, and to not export to a CSV at all.
If you really want CSV, Corb2 would be my first thought. It provides CSV export functionality out of the box. It might be worth digging into why that didn't work for you.
DMSDK might work too, but involves writing code that handles the writing of CSV, which sounds cumbersome to me.
Last option that comes to mind would be Apache NiFi for which there are various MarkLogic Processors. It allows orchestration of data flow very generically. It could be rather overkill for your purpose though.
HTH!
ml-gradle has support for exporting documents and referencing a transform, which can convert each document to CSV - https://github.com/marklogic-community/ml-gradle/wiki/Exporting-data#exporting-data-to-csv .
Unless all of your documents are flat, you likely need some custom code to determine how to map a hierarchical document into a flat row. So a REST transform is a reasonable solution there.
You can also use a TDE template to project your documents into rows, and the /v1/rows endpoint can return results as CSV. That of course requires creating and loading a TDE template, and then waiting for the matching documents to be re-indexed.
I have a large 180k row SQL (mysql) database that I want to use in CoreData. Can I create the SQLite database using Xcode, then use an SQLight client app to connect to that database, and fill it using my mysql data?
Or is there a better way to efficiently import a large data set to a CoreData store?
It will only be filled once and the data should reside on-device.
The reason I want to do this is because I am building an iOS app that needs to read from a persistent store containing most words in the English language. Along with the word, each row will contain a few other things. The app will never need to write to the database, just read from it, but it will need to read from it very quickly.
From Apple's docs it appears this is not recommended (or maybe impossible): "do not manipulate an existing Core Data-created SQLite store using the native SQLite API"
Update:
Another option that I am currently working on is to export the MySQL database to json using phpmyadmin (or another tool). Then load that json file in to the project. When the app loads (hopefully just the first time it is used), push the data from the json file in to Core Data.
You could reverse-engineer Core Data and produce a Core Data sqlite file directly if you really wanted to, but as you quoted from Apple docs this is not a good idea.
It would be easier to simply write a little macOS command-line tool which includes the same Core Data data model as your iOS app. This tool would read your MySQL database and write it to a Core Data SQLite file, which you would then ship with your iOS app.
I am new to GeoMesa. I mean I just typed geomesa command. So, after following the command line tools tutorial on GeoMesa website. I found some information on ingesting data to geomesa through a .csv file.
So, for my research:
I have a MySQL database storing all the information sent from an Android Application.
And I want to perform some geo spatial analytics on it.
Right now I am converting my MySQL table to .csv file and then ingest it into geomesa as adviced on GeoMesa website.
But my questions are:
Is there any other better option because data is in GB and its a streaming data, hence I have to make .csv file regularly?
Is there any API through which I can connect my MySQL database to geomesa?
Is there any way to ingest using .sql dump file because that would be more easier then .csv file?
Since you are dealing with streaming data, I'd point to two GeoMesa integrations:
First, you might want to check out NiFi for managing data flows. If that fits into your architecture, then you can use GeoMesa with NiFi.
Second, Storm is quite popular for working with streaming data. GeoMesa has a brief tutorial for Storm here.
Third, to ingest sql dumps directly, one option would be to extend the GeoMesa converter library to support them. So far, we haven't had that as a feature request from a customer or a contribution to the project. It'd definitely be a sensible and welcome extension!
I'd also point out the GeoMesa gitter channel. It can be useful for quicker responses.
Has anyone had much experience with data migration into and out of NetSuite? I have to export DB2 tables into MySQL, manipulate data, and then export ina CSV file. Then take a CSV file of accounts and manipulate the data again for accounts to match up from our old system to new. Anyone tried to do this in MySQL?
A couple of options:
Invest in a data transformation tool that connects to NetSuite and DB2 or MySQL. Look at Dell Boomi, IBM Cast Iron, etc. These tools allow you to connect to both systems, define the data to be extracted, perform data transformation functions and mappings and do all the inserts/updates or whatever you need to do.
For MySQL to NetSuite, php scripts can be written to access MySQL and NetSuite. On the NetSuite side, you can either do SOAP web services, or you can write custom REST APIs within NetSuite. SOAP is probably a bit slower than REST, but with REST, you have to write the API yourself (server side JavaScript - it's not hard, but there's a learning curve).
Hope this helps.
I'm an IBM i programmer; try CPYTOIMPF to create a pretty generic CSV file. I'll go to a stream file - if you have NetServer running you can map a network drive to the IFS directory or you can use FTP to get the CSV file from the IFS to another machine in your network.
Try Adeptia's Netsuite integration tool to perform ETL. You can also try Pentaho ETL for this (As far as I know Celigo's Netsuite connector is built upon Pentaho). Also Jitterbit does have an extension for Netsuite.
We primarily have 2 options to pump data into NS:
i)SuiteTalk ---> Using which we can have SOAP based transformations.There are 2 versions of SuiteTalk synchronous and asynchronous.
Typical tools like Boomi/Mule/Jitterbit use synchronous SuiteTalk to pump data into NS.They also have decent editors to help you do mapping.
ii)RESTlets ---> which are typical REST based architures by NS can also be used but you may have to write external brokers to communicate with them.
Depending on your need you can have whatever you need.IN most of the cases you will be using SuiteTalk to bring in data to Netsuite.
Hope this helps ...
We just got done doing this. We used an iPAAS platform called Jitterbit (similar to Dell Boomi). It can connect to mySql and to NetSuite and you can do transformations in the tool. I have been really impressed with the platform overall so far
There are different approaches, I like the following to process a batch job:
To import data to Netsuite:
Export CSV from old system and place it in Netsuite's a File Cabinet folder (Use a RESTlet or Webservices for this).
Run a scheduled script to load the files in the folder and update the records.
Don't forget to handle errors. Ways to handle errors: send email, create custom record, log to file or write to record
Once the file has been processed move the file to another folder or delete it.
To export data out of Netsuite:
Gather data and export to a CSV (You can use a saved search or similar)
Place CSV in File Cabinet folder.
From external server call webservices or RESTlet to grab new CSV files in the folder.
Process file.
Handle errors.
Call webservices or RESTlet to move CSV File or Delete.
You can also use Pentaho Data Integration, its free and the learning curve is not that difficult. I took this course and I was able to play around with the tool within a couple of hours.
I have an existing MySQL database, I would like to import the schema into Xcode and create a Core Data data model.
Is there a way (tool, process) to import the CREATE statements so I don't have to build the models "by hand"?
As an intermediary step I could convert to SQLite, I'm not worried about the relationships, foreign keys etc just auto-generating the Entities (Tables) and Properties (Columns).
Actually I needed the feature so badly too that I have decided to make an OSX utility to do so. BUT... then I found a utility in the Mac Appstore that (partially) solves this problem (it was free for some time, I do not know its current state). Its called JSONModeler and what it does is parsing a json tree and generates the coredata model and all derived NSManagedObject subclasses automatically. So a typical workflow would be:
Export the tables from MySQL to xml
Convert the xml to json
Feed the utility with that json and get your coredata model
Now, for a more complicated scenario (relationships etc) I guess you would have to tweak your xml so it would reflect a valid object tree. Then JSONModeler will be able to recreate that tree and export it for coredata.
The problem here is that entities are not tables and properties are not columns. Core Data is an object graph management system and not a database system. The difference is subtle but important. Core Data really doesn't have anything to do with SQL it just sometimes uses SQL as one its persistence options.
Core Data does use a proprietary sqlite schema and in principle you can duplicate that but I don't know of anyone who has succeeded in a robust manner except for very simple SQL databases. Even when they do, its a lot of work. Further, doing so is unsupported and the schema might break somewhere down the line.
The easiest and most robust solution is to write a utility app to read in the existing DB and create the object graph as it goes. You only have to run it once and you've got to create the data model anyway so it doesn't take much time.