indexing-blocks

Tracking every block for time-series analytics involves registering an onBlock handler to capture block context and storing results in BlockSnapshot. You can process each block or sample intervals without needing contract addresses or separate config entries.

Yes, you can sample blocks at intervals by configuring an interval parameter. Setting an interval of 100 processes every 100th block, reducing overhead while still generating time-series snapshots and block-level aggregates for your indexing workflow.

No, you do not need contract addresses or a separate config entry to start block-by-block indexing. The onBlock handler activates by registering for a specific chain and stores results directly in BlockSnapshot without contract address dependencies.

Generating block-level aggregates for historical trends is best done using an onBlock handler with interval-based processing. This captures block context at regular intervals, storing metadata in BlockSnapshot to build time-series datasets for historical analysis.

A key limitation of interval-based block sampling is that processing every Nth block skips interim data, meaning highly granular per-block event tracking is lost. It suits trend analysis but misses fine-grained state changes between sampled intervals.