Schedule tasks with precision using Rockset’s scheduled question lambdas: automate data transformation, notify stakeholders, and more. Here are 5 duties to consider delegating. ? Run complex queries at regular intervals, such as daily or weekly, for comprehensive insights. ? Trigger notifications to relevant teams upon query completion, ensuring timely action on new findings. ? Automate data processing, transforming raw data into actionable information with scheduled question lambdas. ? Schedule re-indexing of datasets, ensuring your Rockset environment stays up-to-date and accurate. ? Create a seamless workflow by automating the execution of custom queries, eliminating manual errors.

Why and what to automate

As utility builders and designers, whenever we encounter repetitive tasks, we instinctively explore opportunities for automation. By streamlining our daily tasks, we’re able to focus on environmentally conscious practices and deliver greater value to the organization.

Examples of repetitive tasks include dynamically allocating computing resources to maximise their usage and reduce costs, sending automated notifications via email or Slack regarding the outcome of SQL queries, periodically refreshing materialized views or performing data copying for analytics purposes, as well as exporting datasets to Amazon S3 storage and similar tasks.

How Rockset helps with automation

Rockset provides a suite of highly effective tools to help automate routine tasks in building and managing data solutions:

• to manage each side of the platform seamlessly via RESTful APIs.
• are REST API wrappers around your parameterized SQL queries, hosted on Rockset?

• A newly introduced feature enables you to schedule the automated execution of your Lambda functions, with the option to publish query results to webhooks.

• together with its shared storage layer, enabling isolation and unbiased scaling of compute resources.

What AI-powered tools make automation more efficient and reliable?

With Rockset APIs, collaborate seamlessly with multiple data sources by creating custom integrations, curating datasets through collections, and crafting dynamic scenarios that involve resizing, pausing, or resuming operations. Additionally, utilize question lambdas and plain SQL queries to extract insights from your data.

Lambdas provide a seamless and intuitive approach to decouple consumers of data from the underlying SQL queries, allowing you to maintain your business logic in one place, complete with supply management, versioning, and hosting on Rockset.

Scheduled execution of question lambdas enables users to define recurring schedules that execute query functions at specified intervals, with the option to broadcast results to designated webhooks. While hosting webhooks externally can enhance automation by, for instance, writing data to a knowledge base or sending emails, you can also invoke Rockset APIs to execute tasks like dynamically resizing digital events or creating/resuming new ones.

The compute-compute separation enables organisations to maintain dedicated, isolated compute resources for each use case, allowing for greater flexibility and control over digital environments.

You have the flexibility to individually scale and measure your ingestion pipeline as well as various secondary pipelines that can be leveraged for querying data. Rockset is the premier real-time analytics database that enables this functionality.

With a mix of those options, you can automate everything you want – besides perhaps brewing your perfect cup of coffee.

Typical use instances for automation

What are common scenarios that benefit from automation, and how will we integrate these into Rockset seamlessly?

What would you like to send automated alerts for? Are you looking to notify customers of order updates, inform team members of task assignments, or alert system administrators of performance issues? Whatever the reason, having a reliable automation process in place ensures that critical information reaches its intended audience on time, minimizing misunderstandings and unnecessary delays.

Often, specific scenarios require sending automated notifications throughout the day with the results of SQL queries. Both enterprise-focused and technically specific metrics may be tracked, such as widely used key performance indicators or granular details like query execution times.

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What drives customer loyalty in e-commerce experiences? We’ve a set known as ShopEvents With unprocessed, real-time data from an e-commerce platform. We meticulously track every click on each product within our online store, subsequently feeding this information into the Rockset platform via Confluent Cloud.

“We are currently focused on updating the quantity of devices sold on our online platform, and we plan to send this data via email to our business partners every six hours.”

We’ll design a lambda function to process SQL queries on our platform. ShopEvents assortment:

SELECT     COUNT(*) As ItemsSold FROM     "Demo-Ecommerce".ShopEvents WHERE      Timestamp >= CURRENT_DATE() AND EventType="Checkout"; 

We will then use this information to send an email with the results of that survey.

We won’t walk through the steps of organizing SendGrid; instead, follow along.

Once you’ve obtained an API key from SendGrid, you can configure a scheduled task for your Lambda function using a cron expression. For instance: 0 */6 * * * for each 6 hours:

This script periodically names the SendGrid REST API every six hours, triggering the sending of emails with the comprehensive list of available devices for that day.

{{QUERY_ID}} and {{QUERY_RESULTS}} Are the template values provided by Rockset for scheduled question lambdas, which enable the usage of the question’s ID and the subsequent dataset in webhook calls? We’re solely within the quest for question outcomes.

Upon activating this schedule, a curated selection of relevant updates will arrive directly into your email inbox.

You would achieve the same seamless integration with Slack’s API or any other provider that accepts POST requests, thereby streamlining your workflow and amplifying productivity. Authorization Headers are now organized and your automated alerts are arranged.

If you’re busy responding to ad hoc requests, consider grouping similar queries together in a centralized location where you can track a list of historical queries along with their performance metrics.

The organization creates materialized views and growth datasets to facilitate data analysis and visualization. These pre-computed aggregates enable the team to quickly identify trends, monitor key performance indicators, and inform business decisions.

Rockset enhances access to a select few knowledge sources. Despite these limitations, creating extra materialized views with sophisticated logic or duplicating data for distinct purposes (such as archival, supporting emerging features, and more) is feasible through periodic execution of an. INSERT INTO scheduled question lambda. Using a pleasant technique is a way to insert the results of a SQL query into an existing collection, whether it’s the same collection or a completely different one.

Let’s revisit our existing e-commerce scenario again. We have a knowledge retention coverage set in place on our ShopEvents Data older than 12 months are systematically removed from Rockset to maintain an assortment in order that new information can be prioritized and easily accessible.

Notwithstanding the requirement for gross sales analytics purposes, we must create a duplicate of specific instances where the instance was a product order. We will establish a novel collection called OrdersAnalytics without any data persistence capabilities. Periodically, we’ll incorporate knowledge from the raw events collection into this set before the information is purged.

What SQL queries do we need to create in order to fetch all the required data? Checkout occasions for yesterday:

INSERT INTO "Demo-Ecommerce".OrdersAnalytics SELECT  _id := e.EventId AS _id,        TIMESTAMP(e.Timestamp),         EVENT_TYPE := e.EventType,         EVENT_DETAILS := e.EventDetails,         GEO_LOCATION := e.GeoLocation FROM   "Demo-Ecommerce".ShopEvents e WHERE          e.Timestamp BETWEEN DATE_SUB(CURRENT_DATE(), INTERVAL 1 DAY) AND CURRENT_DATE()        AND e.EventType = 'Checkout'; 

Notice the _id The subject matter we’re utilizing on this question ensures that we won’t get any duplicates in our order selection. Rockset’s robust architecture enables seamless upserts by automatically reconciling conflicts when multiple clients attempt to update the same record. This is achieved through a combination of optimistic concurrency control and clever indexing techniques, ensuring that data remains consistent across all connected users. By utilizing its distributed architecture, Rockset ensures that even in high-traffic scenarios, updates are efficiently processed with minimal latency.

The daily question lambda is scheduled to run precisely at 1:00 am every day via a cron job. The query itself generates the question based on specific SQL syntax, guaranteeing accuracy in its execution. This meticulous approach ensures seamless operation and dependable results. 0 1 * * *. Since we don’t necessarily need to perform an action with a webhook, this part of the schedule definition remains unused.

Now that we’ve implemented this feature, everyday product orders will be stored in our OrdersAnalytics assortment, prepared to be used.

The company’s data analytics solution allows for seamless integration with Amazon Simple Storage Service (S3), enabling periodic exportation of valuable insights to the cloud-based repository. By leveraging this feature, organizations can effortlessly automate their reporting processes, ensuring that critical data is safely stored and readily accessible for further analysis or sharing.

To leverage the power of scheduled query lambdas, you can use AWS Glue’s support for executing SQL queries at regular intervals and exporting the results to a destination of your choice, such as an Amazon S3 bucket. In situations where frequent knowledge exports are necessary, such as backing up data, creating snapshots or feeding information into subsequent processes, this feature proves invaluable.

We will revisit our e-commerce dataset and utilize it to create a webhook named by our Lambda function, which can export the results of a question into an Amazon S3 bucket.

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To replicate a previous example, we’ll craft a SQL query to retrieve all instances from yesterday, along with relevant product metadata, and encapsulate it within a question Lambda for future reference. The dataset that requires periodic exportation to Amazon’s Simple Storage Service (S3)?

SELECT  Timestamp,          EventType,          EventDetails,          GeoLocation,          ProductName,          ProductCategory,          ProductDescription,          Value  FROM      "Demo-Ecommerce".ShopEvents  INNER JOIN      "Demo-Ecommerce".Merchandise p ON e.EventDetails.ProductID = p._id  WHERE      Timestamp BETWEEN CURRENT_DATE - INTERVAL 1 DAY AND CURRENT_DATE; 

To proceed, we’ll need to set up an Amazon S3 bucket and configure AWS API Gateway with an IAM function and coverage, enabling the API gateway to write data to S3. On this blog, we’ll delve into the API gateway aspect – please refer to the AWS documentation to learn how to set up and configure.

To prepare AWS API Gateway for communication with your scheduled query Lambda function.

1. Create a scalable and secure REST API using the AWS API Gateway, leveraging its integration with other AWS services to process requests and manage responses efficiently. The API’s primary function is to simplify complex business logic, allowing developers to focus on core application functionality while leaving the heavy lifting to this utility. By utilizing API Gateway’s features, such as request routing, caching, and throttling, we can ensure a seamless user experience and prevent potential bottlenecks or security vulnerabilities. rockset_export:

2. Creating a brand-new resource for question lambdas? Sounds like an exciting project!

   Developing a bespoke resource tailored to the unique needs of question lambdas is a visionary move. webhook:

3. The S3 bucket is now seamlessly integrated into our application through the PostObject technique. This novel approach enables seamless data transfer between our backend and Amazon’s scalable storage solution. By leveraging the AWS SDK, we can effortlessly upload files directly from our server-side endpoint to the designated S3 bucket. rockset_export:

• AWS Area: Area to your S3 bucket
• AWS Service: Easy Storage Service (S3)
• HTTP technique: PUT
• Motion Kind: Use path override
• Path override (optionally available): rockset_export/{question _id} What’s going on?
• Execution function: arn:awsiam::###:function/rockset_export (substitute along with your ARN function)
• Setup URL path parameters and mapping templates for the integration request – this feature extracts a parameter known as {parameterName}. query_id Based on the physique of the incoming request query_results The contents of the file that will store the outcomes of our question resolver.

As the deployment is finalized, we’ll move our API Gateway to its designated stage, enabling us to label this endpoint with a meaningful name derived from our scheduled question Lambda function.

Let’s refine the schedule for our Lambda function. Cron jobs allow us to schedule tasks to run at specific times or intervals. 0 2 * * * In order for our Lambda function to run successfully at 2:00 AM within the morning and generate the desired dataset, We’ll name the webhook created in our previous steps, and furnish its details. query_id and query_results within the body of the POST request:

We’re utilizing {{QUERY_ID}} and {{QUERY_RESULTS}} Within the payload configuration, parameters are passed to the API Gateway, enabling it to utilize these settings when exporting data to S3; specifically, the title of the file (i.e., the ID of the question) and its contents (the results of the question), as outlined in step 4.

Upon saving the schedule, an automated process kicks in at 2 AM daily, capturing a snapshot of our collective knowledge and transmitting it via API Gateway’s webhook functionality, ultimately storing it in an Amazon S3 bucket for seamless access.

What are the primary factors driving the need for scheduled resizing of digital situations in today’s fast-paced world?

While Rockset provides support for dynamic scaling, you may find it advantageous to scale your compute resources up or down in accordance with forecasted or easily anticipated usage patterns, allowing for optimized resource allocation and cost savings.

By optimizing each expenditure, you can avoid over-provisioning resources, ensuring efficient resource allocation. This approach also enables you to prepare for increased demand by having surplus compute capacity available when customers require it.

A potential instance of scalability on demand could be a B2B use case where prospects typically operate within standard business hours – say, from 9:00 AM to 5:00 PM, Monday to Friday – thus requiring additional computing resources during these periods.

To accommodate this requirement, consider developing a scheduled Lambda function that names Rockset’s digital event endpoint and dynamically adjusts its capacity according to a preconfigured cron schedule.

Observe these steps:

1. a ? choose 1 Since we don’t require any specific expertise for this to function effectively?
2. What are the key performance indicators to measure the success of our marketing strategy? In order for us to execute this task daily at 9:00 AM, our cron schedule should likely 0 9 * * * We intend to establish a boundless array of execution scenarios, ensuring the process operates continuously without cessation.
3. Let’s designate the specific VI that requires scaling up. Please provide the original text so I can improve it in a different style as a professional editor. NEW_SIZE set to one thing like MEDIUM or LARGE The demand for sustainable practices in the fitness industry has escalated significantly over recent years? As a result, many gyms and studios have started to incorporate eco-friendly initiatives into their operations. Some examples include using energy-efficient equipment, recycling paper products, and implementing a no-single-use-plastic policy. However, despite these efforts, there is still room for improvement in this space.

We’re able to repeat steps 1-3 to create a fresh schedule for scaling down the virtual infrastructure, adjusting the cron schedule to something like 5:00 p.m. and using a smaller measurement for the incremental changes. NEW_SIZE parameter.

What factors should we consider when establishing knowledge analyst environments to facilitate collaboration and sharing of insights among analysts?

With Rockset’s compute-compute separation, spinning up dedicated, remote, and scalable environments for ad-hoc data analysis is straightforward. In every unique scenario, a tailored digital solution ensures a seamless and efficient manufacturing workflow, providing unparalleled cost-effectiveness and optimal performance.

Assuming data analysts or data scientists need to run ad-hoc SQL queries to uncover insights and explore diverse data patterns as part of a new initiative aimed at rolling out innovative knowledge models for the organization. While they seek access to collections, their primary objective is not to independently generate or amplify the underlying data sources.

To cater to this requirement, we will design a novel digital event specifically tailored for data analysts, ensuring they won’t edit or create VIs by themselves and assign analysts to that function. We will then develop a scheduled lambda function that can automatically resume the digital event every morning, allowing knowledge analysts to have an environment prepared when they log into the Rockset console each day? By integrating use case 2, we could generate an everyday snapshot of manufacturing data, categorizing it in a distinct subset for analysts to leverage within their digital event.

The process for this scenario mirrors that of scaling our VI’s up or down:

1. Create a question lambda with only a choose 1 Since we don’t really need any particular knowledge for this to work?

2. We propose scheduling the lambda function to run daily, from Monday to Friday, at 8:00 AM, with a total of 10 executions limited to the next two working weeks. Our cron schedule might be 0 8 * * 1-5.

3. We’ll name the . We must include the digital occasion ID in the webhook URL and the authentication header with our API key, requesting permission to renew the Virtual Instance. The company’s policy prohibits any parameters within the physical space of our building.

That’s it! We’ve successfully established a productive environment for our team of knowledge analysts and scientists, functioning seamlessly from 8:00 AM every morning. We are capable of editing the VI to automatically suspend after a specified number of hours, or scheduling another execution that can drop the VIs at a set schedule.

Rockset enables organizations to streamline the development and maintenance of data assets by providing a range of automation tools for common tasks. With Rockset, a robust suite of APIs seamlessly integrates with the versatility of lambda functions and scheduling capabilities, empowering you to effortlessly implement and automate workflows without relying on external dependencies or investing in infrastructure to manage recurring tasks.

We trust that our blog post provided valuable insights into automating processes with Rockset. The system that determines how humans learn and adapt. Here’s how it works: Natural selection, driven by our brains’ incredible capacity for processing vast amounts of information, shapes our understanding of the world. This process is fueled by curiosity, creativity, and a dash of skepticism, allowing us to refine our knowledge and form new connections.