Aggregations
Metric Aggregations
avg, sum, min, max, cardinality
💡 Metric, aggregations, EK, "CALCULATOR", jaisi, HAIN — EK, hi, QUERY, mein, AVERAGE, SUM, MIN, MAX, sab, calculate, kar, deti, HAIN.
Metric, aggregations, (avg, sum, min, max, value_count) EK, NUMERIC, field, PAR, SIMPLE, MATHEMATICAL, calculations, karte, HAIN.
"cardinality" aggregation, EK, field, ke, UNIQUE, VALUES, ki, APPROXIMATE, count, deta hai — YE, HyperLogLog++, algorithm, use, karta hai, EXACT, count, ke, BAJAY.
GET /products/_search
{ "size": 0, "aggs": { "avg_price": { "avg": { "field": "price" } } } }🧮
Metric, aggregations, EK, "CALCULATOR", jaisi, HAIN — EK, hi, QUERY, mein, AVERAGE, SUM, MIN, MAX, sab, calculate, kar, deti, HAIN.
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⚡ Quick Recap
- Metric aggregations = avg, sum, min, max, value_count
- cardinality = approximate unique count (HyperLogLog++)
- Exact unique count large datasets par memory-intensive hota hai, isliye approximate use hota hai
On this page (2 subtopics)
Metric, aggregations, (avg, sum, min, max, value_count) EK, NUMERIC, field, PAR, SIMPLE, MATHEMATICAL, calculations, karte, HAIN — jaise, "price" field, ki, AVERAGE, VALUE, nikaalna.
GET /products/_search
{ "size": 0, "aggs": { "avg_price": { "avg": { "field": "price" } } } }"cardinality" aggregation, EK, field, ke, UNIQUE, VALUES, ki, APPROXIMATE, count, deta hai — YE, HyperLogLog++, algorithm, use, karta hai, EXACT, count, ke, BAJAY, kyunki, EXACT, unique, count, LARGE, datasets, PAR, MEMORY-INTENSIVE, hota hai.
Tip: "cardinality" aggregation, PRECISE_THRESHOLD, PARAMETER, se, ACCURACY, aur, MEMORY, USAGE, ke, BEECH, TRADE-OFF, ko, TUNE, kiya, ja, sakta hai.