George  Koelpin

George Koelpin

1604132160

A Quick Experiment with the CARTO BigQuery Tiler!

Created with my friend, co-presenter, and fellow data hacker, Julie (twitter), and with help from CARTO!

Hello, world!

Recently, CARTO introduced the BigQuery Tiler and we had the opportunity to present at the Spatial Data Science Conference 2020 and give a glimpse of what the tiler is like.

We gave a talk!

We created a couple demos for this presentation, and we wanted to share it out as a bit of a “hello, world” exercise for the tiler! We have loaded the data and the queries/code onto a Github repository and you’re welcome to give it a whirl. When building these for the first time, we found a lot of good information on a lot of the different components, but it wasn’t always straightforward trying to tie them all together, so this includes a lot of lessons we learned along the way, and gives a full end to end example from data creation to visualization.

There are some important points to review before running the demo. They are listed in the readme file, but it’s worth reiterating here as well:

  • This is demonstration code that is meant to be used to learn, and isn’t meant for use in production. It’s not a supported product, so things may change and break over time, and we’ll try to fix it when we can!
  • If this is your first time using Google Cloud, be sure to start your free trial and have your project created!
  • This uses Google BigQuery, which can incur costs. Be sure to understand how costs will be incurred to your project through the pricing page, and be sure to understand the Google Cloud Trial and Free Tiers as well if this is your first project.
  • This also uses the CARTO BigQuery Tiler. You need to be a part of the beta for this to work. Find more information on this here.
  • You’ll also, of course, need a CARTO account!
  • For tasks done in the command line for Google Cloud and BigQuery, you can leverage the Cloud Shell which has the command line tools pre-installed, or you can install the Google Cloud SDK to your local (or virtual) machine.
  • In the command line, be sure to initialize things by running gcloud auth login to set your user, and gcloud init to set your default project.

#big-data #carto #geospatial #bigquery #data-science

What is GEEK

Buddha Community

A Quick Experiment with the CARTO BigQuery Tiler!
George  Koelpin

George Koelpin

1604132160

A Quick Experiment with the CARTO BigQuery Tiler!

Created with my friend, co-presenter, and fellow data hacker, Julie (twitter), and with help from CARTO!

Hello, world!

Recently, CARTO introduced the BigQuery Tiler and we had the opportunity to present at the Spatial Data Science Conference 2020 and give a glimpse of what the tiler is like.

We gave a talk!

We created a couple demos for this presentation, and we wanted to share it out as a bit of a “hello, world” exercise for the tiler! We have loaded the data and the queries/code onto a Github repository and you’re welcome to give it a whirl. When building these for the first time, we found a lot of good information on a lot of the different components, but it wasn’t always straightforward trying to tie them all together, so this includes a lot of lessons we learned along the way, and gives a full end to end example from data creation to visualization.

There are some important points to review before running the demo. They are listed in the readme file, but it’s worth reiterating here as well:

  • This is demonstration code that is meant to be used to learn, and isn’t meant for use in production. It’s not a supported product, so things may change and break over time, and we’ll try to fix it when we can!
  • If this is your first time using Google Cloud, be sure to start your free trial and have your project created!
  • This uses Google BigQuery, which can incur costs. Be sure to understand how costs will be incurred to your project through the pricing page, and be sure to understand the Google Cloud Trial and Free Tiers as well if this is your first project.
  • This also uses the CARTO BigQuery Tiler. You need to be a part of the beta for this to work. Find more information on this here.
  • You’ll also, of course, need a CARTO account!
  • For tasks done in the command line for Google Cloud and BigQuery, you can leverage the Cloud Shell which has the command line tools pre-installed, or you can install the Google Cloud SDK to your local (or virtual) machine.
  • In the command line, be sure to initialize things by running gcloud auth login to set your user, and gcloud init to set your default project.

#big-data #carto #geospatial #bigquery #data-science

Jenny Jabde

1621251999

Quick Flow Male Enhancement Reviews, Benefits Price & Buy Quick Flow?

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On the off chance that you fall in the subsequent class, Quick Flow Male Enhancement is the thing that your body is needing right now. The recently discovered male arrangement is the difficult solver for numerous types and types of erectile pressure causing brokenness and causes those issues to be rectified and henceforth blessings you with the more youthful sexual variant.

What is Quick Flow Male Enhancement?
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Different results of this class have numerous regular Ingredients in them, yet the ones here in Quick Flow Male Enhancement are truly uncommon and furthermore natural in their reap and produce. This allows you to get the experience of the truth of more profound sex intercourse which you generally thought was a fantasy for you. Positively, this is a demonstrated natural thing, and relying upon it is no place off-base according to specialists. It is time that your body is given valuable minerals as requested by age.

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BigQuery : Petabyte Scale Data warehouse In GCP

In GCP , BigQuery is serverless way of doing petabyte scale analytics. This blog explains about BigQuery data warehouse solution on GCP.

Image for post

Introduction

BigQuery is a data warehouse that is built for the cloud. Its google proprietary data warehouse solution on Google Cloud Platform.

BigQuery is Serverless that means as a customer we don’t have to configure/manage any servers & storage.It will be done behind the scene by google. as a customer, our job is to upload the data and query that means which just focus on business rather than thinking about infrastructure.

BigQuery is not a transactional database like Mysql or Oracle. BigQuery is designed for analytical workloads.

For Example, Query like below is called an analytical query because its purpose is to analyze the data and provide some calculative results like count, max, min, avg, etc.

Here we trying to find titles and total_views for each Wikipedia page.

SELECT title,

count(views) as total_views
FROM
`bigquery-public-data.wikipedia.pageviews_2020`
WHERE
DATE(datehour) = “2020–04–18”
GROUP BY
title
ORDER BY
total_views
DESC;

Analytical queries are very useful in reporting and business intelligence because it provides insights from data based on which Business side can make the tactical decision for the company.

Architecture

Being Serverless we actually don’t need to know about underlying architecture but in knowing it would be helpful for us to optimize our query, cost & performance in some scenarios.

BigQuery is built on top of Google Dremel technology which is used inside google since 2006 in many services in production. (Please refer reference section for the paper)

Dremel is google’s interactive ad-hoc query system which is designed to query read-only data. BigQuery uses Dremel for its execution engine.

Apart from Dremel BigQuery uses Google’s innovative tech like Borg, Colossus File Syste, Jupyter network, and Capacitor.

#introduction-to-bigquery #bigquery-for-beginners #gcp-data-warehousing #data-warehouse #google-bigquery #data analysis

Verda  Conroy

Verda Conroy

1593316800

How to use BigQuery API with your own dataset?

Using Flask and Bigquery APIs to extract data from BigQuery datasets based on user query parameters.

#flask #bigquery #google-cloud-platform #sql #api #bigquery

Best Practices to Enhance Your Mobile App User Experience!!

In terms of UX design, the use of proper visual elements is incredibly important. So, how can you implement great visual elements in accordance with the principles of good UX design? We at AppClues Infotech talk about that right here.

For more info:
Website: https://www.appcluesinfotech.com/
Email: info@appcluesinfotech.com
Call: +1-978-309-9910

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