5 Duties to Automate Utilizing Scheduled Question Lambdas in Rockset


Why and what to automate

As utility builders and designers, at any time when we see repeating duties, we instantly take into consideration how you can automate them. This simplifies our every day work and permits us to be extra environment friendly and targeted on delivering worth to the enterprise.


Typical examples of repeating duties embrace scaling compute assets to optimize their utilization from a value and efficiency perspective, sending automated e-mails or Slack messages with outcomes of a SQL question, materializing views or doing periodic copies of information for growth functions, exporting knowledge to S3 buckets, and so forth.

How Rockset helps with automation

Rockset provides a set of highly effective options to assist automate frequent duties in constructing and managing knowledge options:

  • a wealthy set of APIs so that each facet of the platform could be managed by REST
  • Question Lambdas – that are REST API wrappers round your parametrized SQL queries, hosted on Rockset
  • scheduling of Question Lambdas – a lately launched function the place you possibly can create schedules for computerized execution of your question lambdas and submit outcomes of these queries to webhooks
  • compute-compute separation (together with a shared storage layer) which permits isolation and impartial scaling of compute assets

Let’s deep dive into why these are useful for automation.

Rockset APIs mean you can work together with your whole assets – from creating integrations and collections, to creating digital cases, resizing, pausing and resuming them, to operating question lambdas and plain SQL queries.

Question Lambdas provide a pleasant and simple to make use of solution to decouple shoppers of information from the underlying SQL queries to be able to maintain what you are promoting logic in a single place with full supply management, versioning and internet hosting on Rockset.

Scheduled execution of question lambdas lets you create cron schedules that may mechanically execute question lambdas and optionally submit the outcomes of these queries to webhooks. These webhooks could be hosted externally to Rockset (to additional automate your workflow, for instance to jot down knowledge again to a supply system or ship an e-mail), however you can too name Rockset APIs and carry out duties like digital occasion resizing and even creating or resuming a digital occasion.

Compute-compute separation permits you to have devoted, remoted compute assets (digital cases) per use case. This implies you possibly can independently scale and measurement your ingestion VI and a number of secondary VIs which can be used for querying knowledge. Rockset is the primary real-time analytics database to supply this function.

With the mix of those options, you possibly can automate the whole lot you want (besides perhaps brewing your espresso)!

Typical use instances for automation

Let’s now have a look into typical use instances for automation and present how you’ll implement them in Rockset.

Use case 1: Sending automated alerts

Usually instances, there are necessities to ship automated alerts all through the day with outcomes of SQL queries. These could be both enterprise associated (like frequent KPIs that the enterprise is fascinated about) or extra technical (like discovering out what number of queries ran slower than 3 seconds).

Utilizing scheduled question lambdas, we are able to run a SQL question in opposition to Rockset and submit the outcomes of that question to an exterior endpoint similar to an e-mail supplier or Slack.

Let’s have a look at an e-commerce instance. We now have a set known as ShopEvents with uncooked real-time occasions from a webshop. Right here we observe each click on to each product in our webshop, after which ingest this knowledge into Rockset by way of Confluent Cloud. We’re fascinated about understanding what number of objects have been bought on our webshop at present and we need to ship this knowledge by way of e-mail to our enterprise customers each six hours.


We’ll create a question lambda with the next SQL question on our ShopEvents assortment:

    COUNT(*) As ItemsSold
    Timestamp >= CURRENT_DATE() AND EventType="Checkout";

We’ll then use SendGrid to ship an e-mail with the outcomes of that question. We gained’t undergo the steps of establishing SendGrid, you possibly can observe that in their documentation.

When you’ve received an API key from SendGrid, you possibly can create a schedule on your question lambda like this, with a cron schedule of 0 */6 * * * for each 6 hours:


This can name the SendGrid REST API each 6 hours and can set off sending an e-mail with the full variety of bought objects that day.

{{QUERY_ID}} and {{QUERY_RESULTS}} are template values that Rockset offers mechanically for scheduled question lambdas to be able to use the ID of the question and the ensuing dataset in your webhook calls. On this case, we’re solely within the question outcomes.

After enabling this schedule, that is what you’ll get in your inbox:


You possibly can do the identical with Slack API or another supplier that accepts POST requests and Authorization headers and also you’ve received your automated alerts arrange!

If you happen to’re fascinated about sending alerts for gradual queries, have a look at establishing Question Logs the place you possibly can see an inventory of historic queries and their efficiency.

Use case 2: Creating materialized views or growth datasets

Rockset helps computerized real-time rollups on ingestion for some knowledge sources. Nevertheless, when you’ve got a must create extra materialized views with extra advanced logic or if you must have a duplicate of your knowledge for different functions (like archival, growth of recent options, and many others.), you are able to do it periodically through the use of an INSERT INTO scheduled question lambda. INSERT INTO is a pleasant solution to insert the outcomes of a SQL question into an current assortment (it might be the identical assortment or a totally totally different one).

Let’s once more have a look at our e-commerce instance. We now have a knowledge retention coverage set on our ShopEvents assortment in order that occasions which can be older than 12 months mechanically get faraway from Rockset.


Nevertheless, for gross sales analytics functions, we need to make a copy of particular occasions, the place the occasion was a product order. For this, we’ll create a brand new assortment known as OrdersAnalytics with none knowledge retention coverage. We’ll then periodically insert knowledge into this assortment from the uncooked occasions assortment earlier than the information will get purged.


We are able to do that by making a SQL question that may get all Checkout occasions for the day prior to this:

INSERT INTO "Demo-Ecommerce".OrdersAnalytics
    e.EventId AS _id,
    "Demo-Ecommerce".ShopEvents e
    AND e.EventType="Checkout";

Word the _id discipline we’re utilizing on this question – it will be sure that we don’t get any duplicates in our orders assortment. Try how Rockset mechanically handles upserts right here.

Then we create a question lambda with this SQL question syntax, and create a schedule to run this as soon as a day at 1 AM, with a cron schedule 0 1 * * *. We don’t must do something with a webhook, so this a part of the schedule definition is empty.


That’s it – now we’ll have every day product orders saved in our OrdersAnalytics assortment, prepared to be used.

Use case 3: Periodic exporting of information to S3

You need to use scheduled question lambdas to periodically execute a SQL question and export the outcomes of that question to a vacation spot of your alternative, similar to an S3 bucket. That is helpful for situations the place you must export knowledge frequently, similar to backing up knowledge, creating stories or feeding knowledge into downstream programs.

On this instance, we are going to once more work on our e-commerce dataset and we’ll leverage AWS API Gateway to create a webhook that our question lambda can name to export the outcomes of a question into an S3 bucket.


Just like our earlier instance, we’ll write a SQL question to get all occasions from the day prior to this, be part of that with product metadata and we’ll save this question as a question lambda. That is the dataset we need to periodically export to S3.

    "Demo-Ecommerce".ShopEvents e
    INNER JOIN "Demo-Ecommerce".Merchandise p ON e.EventDetails.ProductID = p._id

Subsequent, we’ll must create an S3 bucket and arrange AWS API Gateway with an IAM Position and Coverage in order that the API gateway can write knowledge to S3. On this weblog, we’ll give attention to the API gateway half – be sure you test the AWS documentation on how you can create an S3 bucket and the IAM position and coverage.

Observe these steps to arrange AWS API Gateway so it’s prepared to speak with our scheduled question lambda:

  1. Create a REST API utility within the AWS API Gateway service, we are able to name it rockset_export:


  1. Create a brand new useful resource which our question lambdas will use, we’ll name it webhook:


  1. Create a brand new POST technique utilizing the settings beneath – this primarily permits our endpoint to speak with an S3 bucket known as rockset_export:


  • AWS Area: Area on 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} (exchange together with your bucket title)
  • Execution position: arn:awsiam::###:position/rockset_export (exchange together with your ARN position)
  • Setup URL Path Parameters and Mapping Templates for the Integration Request – it will extract a parameter known as query_id from the physique of the incoming request (we’ll use this as a reputation for recordsdata saved to S3) and query_results which we’ll use for the contents of the file (that is the results of our question lambda):


As soon as that’s executed, we are able to deploy our API Gateway to a Stage and we’re now able to name this endpoint from our scheduled question lambda.

Let’s now configure the schedule for our question lambda. We are able to use a cron schedule 0 2 * * * in order that our question lambda runs at 2 AM within the morning and produces the dataset we have to export. We’ll name the webhook we created within the earlier steps, and we’ll provide query_id and query_results as parameters within the physique of the POST request:


We’re utilizing {{QUERY_ID}} and {{QUERY_RESULTS}} within the payload configuration and passing them to the API Gateway which can use them when exporting to S3 because the title of the file (the ID of the question) and its contents (the results of the question), as described in step 4 above.

As soon as we save this schedule, we’ve an automatic job that runs each morning at 2 AM, grabs a snapshot of our knowledge and sends it to an API Gateway webhook which exports this to an S3 bucket.

Use case 4: Scheduled resizing of digital cases

Rockset has help for auto-scaling digital cases, but when your workload has predictable or nicely understood utilization patterns, you possibly can profit from scaling your compute assets up or down primarily based on a set schedule.

That manner, you possibly can optimize each spend (so that you simply don’t over-provision assets) and efficiency (so that you’re prepared with extra compute energy when your customers need to use the system).

An instance might be a B2B use case the place your clients work primarily in enterprise hours, let’s say 9 AM to five PM all through the work days, and so that you want extra compute assets throughout these instances.

To deal with this use case, you possibly can create a scheduled question lambda that may name Rockset’s digital occasion endpoint and scale it up and down primarily based on a cron schedule.


Observe these steps:

  1. Create a question lambda with only a choose 1 question, since we don’t really need any particular knowledge for this to work.
  2. Create a schedule for this question lambda. In our case, we need to execute as soon as a day at 9 AM so our cron schedule shall be 0 9 * * * and we are going to set limitless variety of executions in order that it runs on daily basis indefinitely.
  3. We’ll name the replace digital occasion webhook for the particular VI that we need to scale up. We have to provide the digital occasion ID within the webhook URL, the authentication header with the API key (it wants permissions to edit the VI) and the parameter with the NEW_SIZE set to one thing like MEDIUM or LARGE within the physique of the request.


We are able to repeat steps 1-3 to create a brand new schedule for scaling the VI down, altering the cron schedule to one thing like 5 PM and utilizing a smaller measurement for the NEW_SIZE parameter.

Use case 5: Establishing knowledge analyst environments

With Rockset’s compute-compute separation, it’s simple to spin up devoted, remoted and scalable environments on your advert hoc knowledge evaluation. Every use case can have its personal digital occasion, making certain {that a} manufacturing workload stays secure and performant, with one of the best price-performance for that workload.

On this situation, let’s assume we’ve knowledge analysts or knowledge scientists who need to run advert hoc SQL queries to discover knowledge and work on numerous knowledge fashions as a part of a brand new function the enterprise desires to roll out. They want entry to collections they usually want compute assets however we don’t need them to create or scale these assets on their very own.

To cater to this requirement, we are able to create a brand new digital occasion devoted to knowledge analysts, be sure that they will’t edit or create VIs by making a customized RBAC position and assign analysts to that position, and we are able to then create a scheduled question lambda that may resume the digital occasion each morning in order that knowledge analysts have an setting prepared after they log into the Rockset console. We might even couple this with use case 2 and create a every day snapshot of manufacturing right into a separate assortment and have the analysts work on that dataset from their digital occasion.


The steps for this use case are just like the one the place we scale the VIs up and down:

  1. Create a question lambda with only a choose 1 question, since we don’t really need any particular knowledge for this to work.
  2. Create a schedule for this question lambda, let’s say every day at 8 AM Monday to Friday and we are going to restrict it to 10 executions as a result of we would like this to solely work within the subsequent 2 working weeks. Our cron schedule shall be 0 8 * * 1-5.
  3. We’ll name the resume VI endpoint. We have to provide the digital occasion ID within the webhook URL, the authentication header with the API key (it wants permissions to renew the VI). We don’t want any parameters within the physique of the request.


That’s it! Now we’ve a working setting for our knowledge analysts and knowledge scientists that’s up and operating for them each work day at 8 AM. We are able to edit the VI to both auto-suspend after sure variety of hours or we are able to have one other scheduled execution which can droop the VIs at a set schedule.

As demonstrated above, Rockset provides a set of helpful options to automate frequent duties in constructing and sustaining knowledge options. The wealthy set of APIs mixed with the facility of question lambdas and scheduling mean you can implement and automate workflows which can be utterly hosted and operating in Rockset so that you simply don’t should depend on third celebration parts or arrange infrastructure to automate repeating duties.

We hope this weblog gave you a couple of concepts on how you can do automation in Rockset. Give this a try to tell us the way it works!