I am trying to create BigQuery Data transfer config for Google Adwords through API using a programming language (Python, Java). I looked at the documentation about BigQuery data transfer API. But there is no proper process for that. Maybe I could not understand properly. Can anyone help me in understanding how to use API to get daily analytic data from YouTube instead of paying YouTube to use their BigQuery Data transfer?
You need to get started using Adwords SQL
https://developers.google.com/adwords/api/docs/guides/first-api-call
Refer to the Getting Started section of the Python client library README file to download and install the AdWords API client library for Python.
Related
I have been trying to build a pipeline in Google Cloud Data Fusion where data source is a 3rd party API endpoint. I have been unable to successfully use the HTTP Plugin, but it has been suggested that I use Pub/Sub for the data ingest.
I've been trying to follow this tutorial as a starting point, but it doesn't help me out with the very first step of the process: ingesting data from API endpoint.
Can anyone provide examples of using Pub/Sub -- or any other viable method -- to ingest data from an API endpoint and send that data down to Data Fusion for transformation and ultimately to BigQuery?
I will also need to be able to dynamically modify the URI (e.g., date filter parameters) in the GET request in this pipeline.
In order to achieve the first step in the tutorial you are following
Ingest CSV (Comma-separated values) data to BigQuery using Cloud Data Fusion.
You need to set up a functioning pub/sub system. This can be done via the command line, the console, or in your case the best would be to use, one of the client libraries. If you follow this tutorial you should have a functioning pub/sub system.
At that point you should be able to follow the original tutorial
Basically, i want to get analytic reports through YouTube API by using Python. After hours searching how to make it happend. I am known that YouTube just supporting API through their graphical design, which is really limited.
Please advised me, is there any way to get daily/weekly/monthly report by using Python?
FYI, at the moment, i am using YouTube's service to automatically update the reports into my database which is BigTable.
Currently was playing around with a robotic process application called Blue Prism and learned you can drop a URL link to a WSDL location to consume api calls. I tested using a free service and it worked great.
My question is in regards to Google Sheets API, a project has come up where this would be very usefull however I'm not able to locate or if one even exists (A WSDL or WADL) for the google sheets api.
If anyone could give me any direction on this that would be fantastic.
Google docs can be automated using REST web services. You can find more information about google docs api at google sheets API page.
BluePrism has an out-of-box tools to work with SOAP request with WSDL, but unfortunately it does not have out-of-box support for REST web services.
If you'd like to use API to interact with google docs, then you can do that, but you'll have to create your own code stages to do that.
I am using google-api-php-client-services to train my data of my PHP website in google cloud. How do I do preprocessing in https://cloud.google.com/blog/big-data/2016/12/how-to-classify-images-with-tensorflow-using-google-cloud-machine-learning-and-cloud-dataflow using this library?
Is there any alternative to google-api-php-client to interact with ml_engine in PHP?
That is the only client library available for CMLE. But that client library only provides PHP wrappers for Google Cloud APIs such as CMLE's API
The actual preprocessing done in the blog post is written as a Dataflow job in Python. As the blog post describes to run it you have to execute a Python program.
You won't be able to write your Dataflow job using PHP.
I am new to Google Cloud Platforms and not quite sure with the whole architecture but what I am trying to achieve is to save some data to Google Cloud from an iOS application and do some analytics work on this data using Google Cloud Products, such as: Dataproc and Datalab. From what I read so far I would need to create a dataset in Google Cloud BigQuery and create a table in it. I have done this using the Google Cloud Web UI but now I want to populate the table from my iOS app. I can't seem to find how to do that.
The most painless route would be to wire up Firebase Analytics and then turn on its daily log export to Big Query, as described by Google in the walkthrough Importing Firebase Analytics Data into BigQuery. Google maintains the entire analytic export stack for you then, seeing as they also maintain Firebase. The downside is that the analytics export happens only daily.
Alternatively, you'd be looking at using the Big Query REST API to upload data, as documented by Google in their Loading Data with a POST Request how-to guide. The iOS tooling for that would be your usual NSURLSession and NSURLDataTask APIs, or whatever abstraction you prefer that's built atop them.
Google does maintain a collection of iOS-native APIs, but unfortunately, Big Query is not included amongst the supported APIs as of May 2017. There are native Big Query clients for Go, C#, and Java, amongst others. So you could use your own API for upload to a server you control, and then use one of those client APIs serverside to implement the actual Big Query integration, if you wished.