Reading SQL Query Plans for Blockchain Analytics
Measure scans, joins and row estimates before optimising blockchain queries, and preserve the result contract while improving execution performance.
Overview
When translating these concepts into an integration, keep the scope described by the wallet history api with the result. The examples in wallet transaction history and smart contract event logs show how the same distinction affects neighbouring data questions.
A slow analytical query can be limited by scanning, join expansion, sorting or inaccurate estimates. A query plan helps identify the actual cost instead of guessing from the SQL length.
Inspect the dominant work
Check selected partitions, rows scanned, join cardinality and sort behaviour. Compare estimates with measured execution in an isolated environment. Production-like data distribution matters: a popular token can have very different selectivity from a rarely used contract. An index useful for one predicate may not help another.
Worked example: filtering too late
A query joins a large transfer table before restricting one network and block range. Pushing compatible filters into the relevant input can reduce work, but verify that outer-join and missing-data semantics remain unchanged. A faster query that drops unresolved price rows is not an equivalent optimisation.
Verify correctness after tuning
Compare evidence IDs, counts and exact totals before and after the change. Test an empty range and dense event blocks. Use bounded benchmarks rather than uncontrolled live scans. Keep execution performance separate from chain-data freshness: a fast query over incomplete data can still answer the wrong question.
A practical acceptance test
Benchmark a bounded fixture with one dense asset and one sparse asset. Compare query plans and exact result identities before and after optimisation. Include missing-price rows so moving a filter across an outer join cannot silently drop them. Faster runtime is accepted only if the declared semantic result and coverage remain the same.
Questions about the topic
Frequently asked questions
Does shorter SQL always run faster?
No. Execution plans and data distribution determine the work.
Can moving a filter change results?
Yes, especially around joins and missing values; verify semantic equivalence.
Standards & technical documentation
