5 Duties to Automate Utilizing Scheduled Question Lambdas in Rockset

Why and what to automate

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


Typical examples of repeating duties embody scaling compute sources to optimize their utilization from a price 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 information to S3 buckets, and so forth.

How Rockset helps with automation

Rockset gives a set of highly effective options to assist automate widespread duties in constructing and managing information options:

  • a wealthy set of APIs so that each side of the platform could be managed by means of REST
  • Question Lambdas – that are REST API wrappers round your parametrized SQL queries, hosted on Rockset
  • scheduling of Question Lambdas – a not too long ago launched characteristic the place you may 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 sources

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

Rockset APIs will let you work together with your entire sources – from creating integrations and collections, to creating digital cases, resizing, pausing and resuming them, to operating question lambdas and plain SQL queries.

Question Lambdas supply a pleasant and straightforward to make use of method to decouple customers of information from the underlying SQL queries with the intention to hold your enterprise 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 information again to a supply system or ship an e-mail), however you too can name Rockset APIs and carry out duties like digital occasion resizing and even creating or resuming a digital occasion.

Compute-compute separation means that you can have devoted, remoted compute sources (digital cases) per use case. This implies you may independently scale and dimension your ingestion VI and a number of secondary VIs which can be used for querying information. Rockset is the primary real-time analytics database to supply this characteristic.

With the mix of those options, you may automate every part you want (besides perhaps brewing your espresso)!

Typical use circumstances for automation

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

Use case 1: Sending automated alerts

Usually occasions, there are necessities to ship automated alerts all through the day with outcomes of SQL queries. These could be both enterprise associated (like widespread KPIs that the enterprise is desirous 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 corresponding to an e-mail supplier or Slack.

Let’s have a look at an e-commerce instance. Now we have a set known as ShopEvents with uncooked real-time occasions from a webshop. Right here we monitor each click on to each product in our webshop, after which ingest this information into Rockset by way of Confluent Cloud. We’re desirous about understanding what number of gadgets have been bought on our webshop at the moment and we wish to ship this information 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 organising SendGrid, you may observe that in their documentation.

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


It will name the SendGrid REST API each 6 hours and can set off sending an e-mail with the overall variety of bought gadgets that day.

{{QUERY_ID}} and {{QUERY_RESULTS}} are template values that Rockset supplies mechanically for scheduled question lambdas with the intention 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 would do the identical with Slack API or some other supplier that accepts POST requests and Authorization headers and also you’ve obtained your automated alerts arrange!

For those who’re desirous about sending alerts for sluggish queries, have a look at organising Question Logs the place you may 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 information sources. Nevertheless, when you’ve got a have to create further materialized views with extra complicated logic or if it is advisable to have a replica of your information 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 method to insert the outcomes of a SQL question into an present assortment (it may very well be the identical assortment or a very totally different one).

Let’s once more have a look at our e-commerce instance. Now we have an information 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 wish 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 information retention coverage. We’ll then periodically insert information into this assortment from the uncooked occasions assortment earlier than the info will get purged.


We will do that by making a SQL question that may get all Checkout occasions for the day before today:

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

Observe the _id discipline we’re utilizing on this question – this may 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 have to do something with a webhook, so this a part of the schedule definition is empty.


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

Use case 3: Periodic exporting of information to S3

You should use scheduled question lambdas to periodically execute a SQL question and export the outcomes of that question to a vacation spot of your selection, corresponding to an S3 bucket. That is helpful for eventualities the place it is advisable to export information regularly, corresponding to backing up information, creating stories or feeding information into downstream methods.

On this instance, we’ll 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.


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

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

Subsequent, we’ll have to create an S3 bucket and arrange AWS API Gateway with an IAM Function and Coverage in order that the API gateway can write information to S3. On this weblog, we’ll concentrate on the API gateway half – make sure you test the AWS documentation on how you can create an S3 bucket and the IAM function and coverage.

Comply with 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 methodology utilizing the settings under – this basically 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 methodology: PUT
  • Motion Sort: Use path override
  • Path override (elective): rockset_export/{question _id} (exchange along with your bucket title)
  • Execution function: arn:awsiam::###:function/rockset_export (exchange along with your ARN function)
  • Setup URL Path Parameters and Mapping Templates for the Integration Request – this may extract a parameter known as query_id from the physique of the incoming request (we’ll use this as a reputation for information 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 accomplished, 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 will 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 have now an automatic process that runs each morning at 2 AM, grabs a snapshot of our information 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 may profit from scaling your compute sources up or down primarily based on a set schedule.

That approach, you may optimize each spend (so that you simply don’t over-provision sources) and efficiency (so that you’re prepared with extra compute energy when your customers wish to use the system).

An instance may very well 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 sources throughout these occasions.

To deal with this use case, you may 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.


Comply with these steps:

  1. Create a question lambda with only a choose 1 question, since we don’t really need any particular information for this to work.
  2. Create a schedule for this question lambda. In our case, we wish to execute as soon as a day at 9 AM so our cron schedule will likely be 0 9 * * * and we’ll set limitless variety of executions in order that it runs day by day indefinitely.
  3. We’ll name the replace digital occasion webhook for the precise VI that we wish 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 will 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 dimension for the NEW_SIZE parameter.

Use case 5: Establishing information analyst environments

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

On this state of affairs, let’s assume we have now information analysts or information scientists who wish to run advert hoc SQL queries to discover information and work on varied information fashions as a part of a brand new characteristic the enterprise needs to roll out. They want entry to collections they usually want compute sources however we don’t need them to create or scale these sources on their very own.

To cater to this requirement, we are able to create a brand new digital occasion devoted to information analysts, be sure that they’ll’t edit or create VIs by making a customized RBAC function and assign analysts to that function, and we are able to then create a scheduled question lambda that may resume the digital occasion each morning in order that information analysts have an setting prepared after they log into the Rockset console. We may even couple this with use case 2 and create a each 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 much 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 information for this to work.
  2. Create a schedule for this question lambda, let’s say each day at 8 AM Monday to Friday and we’ll 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 will likely 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 have now a working setting for our information analysts and information scientists that’s up and operating for them each work day at 8 AM. We will 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 gives a set of helpful options to automate widespread duties in constructing and sustaining information options. The wealthy set of APIs mixed with the ability of question lambdas and scheduling will let you implement and automate workflows which can be utterly hosted and operating in Rockset so that you simply don’t should depend on third social gathering elements or arrange infrastructure to automate repeating duties.

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

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