I find Qubole is well suited for getting started analyzing data in the cloud without being locked in to a specific cloud vendor's tooling other than the underlying filesystem. Since the data itself is not isolated to any Qubole cluster, it can be easily be collected back into a cloud-vendor's specific tools for further analysis, therefore I find it complementary to any offerings such as Amazon EMR or Google DataProc.
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React is a JavaScript user interface construction library that works well for:
Developing web apps with dynamic and complicated user interfaces.
creating reusable UI elements that may be used in other applications.
creating single-page applications with dynamic content updates that don't require a page reload.
The Virtual DOM's effective updating mechanism allows it to handle large volumes of data updates.
React, on the other hand, might be less suitable for:
Websites that are simple, stagnant, and have no interaction. Other libraries or simple HTML, CSS, and JavaScript may be a better fit in such circumstances.
Web sockets may be a better choice for applications that need real-time updates, such as chat or gaming apps.
When creating mobile apps, React Native is a better option.
Server side rendering only, as React is designed to run on the client side.
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React is fantastic for building performant user interfaces. Our web app is snappy and great for our customers.
React has the philosophy of doing one thing and doing it well which is the view layer of the application. This makes it incredibly intuitive and flexible for developers to use.
React has lead the way in being able to write modular and structured code. It is a drastic improvement since the days of spaghetti jQuery code.
React has an unmatched community. The amount of tools and libraries available is fantastic, and there plenty of solutions available online for common problems.
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Providing an open selection of all cloud provider instance types with no explanation as to their ideal use cases causes too much confusion for new users setting up a new cluster. For example, not everyone knows that Amazon's R or X-series models are memory optimized, while the C and M-series are for general computation.
I would like to see more ETL tools provided other than DistCP that allow one to move data between Hadoop Filesystems.
From the cluster administration side, onboarding of new users for large companies seems troublesome, especially when trying to create individual cluster per team within the company. Having the ability to debug and share code/queries between users of other teams / clusters should also be possible.
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Debugging React is challenging. Bugs in react code generate stack traces internal to React and it is often totally unclear how it relates to the code you actually wrote.
Relating your React elements to corresponding DOM elements is difficult. The intentional separation of virtual and actual DOM also makes it difficult to map the elements to the structures in the DOM. This is partially ameliorated by the use of the React dev tool, which provides a DOM-like view of the React elements, but the tool still does not provide a direct correspondence with the DOM that is often necessary to figure out why something isn't right.
Because JSX is React-specific and not a language feature, a special compilation process is necessary to convert JSX code to normal JS. Coming from a C++ background, compiling things doesn't bother me, but many JS developers are used to a less structured development.
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Personally, I have no issues using Amazon EMR with Hue and Zeppelin, for example, for data science and exploratory analysis. The benefits to using Qubole are that it offers additional tooling that may not be available in other cloud providers without manual installation and also offers auto-terminating instances and scaling groups.
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React is just a bit of a different animal. I was avoiding it for the longest time. I thought for sure I would land on Vue or something else with a more approachable and familiar appearance. But after taking an online course in React, I started realize what people were raving about (and complaining about) and decided to implement it at our office for one of our products.
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Since it's open-source and very popular, the community support for React and related tools and libraries is excellent. There are a lot of people using the same tools, and so issues tend to get fixed quickly and "recipes" are easy to come by. And since it's backed by Facebook, they have a dedicated engineering team working on the progression of React.
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Qubole was decided on by upper management rather than these competitive offerings. I find that Databricks has a better Spark offering compared to Qubole's Zeppelin notebooks.
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While this is a widely contested debate with various blog posts and benchmarks all over the place, its really a personal choice to determine what works for the team. Coming from a Angular 1.x background, I decided to try a new framework when Angular 2.x was announced and at that time React is gaining popularity and Vue hasn't taken off yet. Compared to Angular 1.x and Vue (hybrid of React and Angular) that split the logic from the html templates, I loved the way React breaks code into components using the jsx syntax. In my mind, this allows for cleaner components and easier maintenance
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
We like to say that Qubole has allowed for "data democratization", meaning that each team is responsible for their own set of tooling and use cases rather than being limited by versions established by products such as Hortonworks HDP or Cloudera CDH
One negative impact is that users have over-provisioned clusters without realizing it, and end up paying for it. When setting up a new cluster, there are too many choices to pick from, and data scientists may not understand the instance types or hardware specs for the datasets they need to operate on.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
