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Filter items by array values in Elasticsearch

This is real work, not a feature someone invented — it comes from real job ads and real questions people asked. Below are four ready AI prompts: get it done, make it easy for the next person to say yes to, work out the right move when you are stuck, and stop it coming back.

4prompts
See the prompt↓All Elasticsearch tasks

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskFilter the 'logs-2023-10-26' index to show only documents where the 'tags' field contains both…+
Filter the 'logs-2023-10-26' index to show only documents where the 'tags' field contains both 'error' and 'critical'.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
BImprove — make it easier to acceptBefore I hand this over to the ops team, show me how to filter the 'logs-2023-10-26' index for…+
Before I hand this over to the ops team, show me how to filter the 'logs-2023-10-26' index for documents where the 'tags' field contains 'error' or 'warning', but make sure the query is efficient for millions of documents and easy for them to adapt for other tag combinations.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentThe dev team is complaining that their filters on the 'events' index are taking too long.…+
The dev team is asking why their filters are slow, and I'm not sure if it's the query or the data structure.
The dev team is complaining that their filters on the 'events' index are taking too long. They're trying to find documents where the 'categories' array contains 'billing' and 'payment_failed'. I'm worried it's either an inefficient query or the mapping is wrong for array fields. What's the most likely diagnosis and the best way to test if the mapping is the problem without disrupting production?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI often build queries that filter documents based on multiple values within an array field, and…+
I keep building complex array filters that perform poorly later.
I often build queries that filter documents based on multiple values within an array field, and they frequently become performance bottlenecks as data grows. What habit should I change in how I approach indexing or querying array fields to avoid these slowdowns in the future?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Questions people actually ask

honest answers, no sign-up

Every task here was seen in the real world. Someone doing the job named it, a real job ad asked for it, or a lot of people asked about it online.

If nothing real showed a task, it is not on the page. That is the whole rule.

They are the same job approached four ways, because what you need depends on where you are.

Get it done today. Make it easy for the next person to say yes to. Work out the right move when you are stuck. Learn the pattern so the job stops coming back.

For most of these jobs it can carry the heavy thinking - draft it, sort it, check it, rehearse it with you.

It cannot sit in your chair, take the blame when a number is wrong, or notice what nobody wrote down. Let it do the first 80%. Keep the last 20% that is truly yours.

No. Copy any prompt and paste it into the AI you already use. No account, no score, no wall in the way.

Any of them. The prompts describe the work rather than naming a product, so they are not tied to one assistant.

That is also why they keep working when you switch.

Change it freely. Every prompt is a starting line, not a rule.

Put in your real numbers, your real names and your real deadline. The more you make it yours, the better the answer comes back.

The tasks come from real job ads, published job data and the questions people ask in public forums.

The steps come from Elasticsearch's own documentation, with practitioner sources for the traps the manual does not mention.

Push once. Ask it to sharpen the weakest part and to say what it assumed.

Most wrong answers come from a missing detail rather than a bad prompt - tell it the thing it could not know.