Dataframe queries 3: dense range

[teh-cmc]

Implements the dense range dataframe APIs.

Examples:

cargo r --all-features -p re_dataframe --example range -- /tmp/data.rrd /helix/structure/scaffolding/beads
cargo r --all-features -p re_dataframe --example range -- /tmp/data.rrd /helix/structure/scaffolding/beads /helix/structure/scaffolding/**

use itertools::Itertools as _;

use re_chunk_store::{
    ChunkStore, ChunkStoreConfig, ComponentColumnDescriptor, RangeQueryExpression, Timeline,
    VersionPolicy,
};
use re_dataframe::QueryEngine;
use re_log_types::{ResolvedTimeRange, StoreKind};

fn main() -> anyhow::Result<()> {
    let args = std::env::args().collect_vec();

    let get_arg = |i| {
        let Some(value) = args.get(i) else {
            eprintln!(
                "Usage: {} <path_to_rrd_with_position3ds> <entity_path_pov> [entity_path_expr]",
                args.first().map_or("$BIN", |s| s.as_str())
            );
            std::process::exit(1);
        };
        value
    };

    let path_to_rrd = get_arg(1);
    let entity_path_pov = get_arg(2).as_str();
    let entity_path_expr = args.get(3).map_or("/**", |s| s.as_str());

    let stores = ChunkStore::from_rrd_filepath(
        &ChunkStoreConfig::DEFAULT,
        path_to_rrd,
        VersionPolicy::Warn,
    )?;

    for (store_id, store) in &stores {
        if store_id.kind != StoreKind::Recording {
            continue;
        }

        let cache = re_dataframe::external::re_query::Caches::new(store);
        let engine = QueryEngine {
            store,
            cache: &cache,
        };

        let query = RangeQueryExpression {
            entity_path_expr: entity_path_expr.into(),
            timeline: Timeline::log_tick(),
            time_range: ResolvedTimeRange::new(0, 30),
            pov: ComponentColumnDescriptor::new::<re_types::components::Position3D>(
                entity_path_pov.into(),
            ),
        };

        let query_handle = engine.range(&query, None /* columns */);
        eprintln!("{query}:");
        for batch in query_handle.into_iter() {
            eprintln!("{batch}");
        }
    }

    Ok(())
}

• Fixes New ChunkStore APIs to facilitate data access #7284

---

Dataframe APIs PR series:

• Dataframe queries 0: bootstrap & data model #7338
• Dataframe queries 1: schema resolution #7339
• Dataframe queries 2: latest-at #7340
• Dataframe queries 3: dense range #7341
• Dataframe queries 4: paginated dense range #7345

Checklist

• I have read and agree to Contributor Guide and the Code of Conduct
• I've included a screenshot or gif (if applicable)
• I have tested the web demo (if applicable):
  • Using examples from latest main build: rerun.io/viewer
  • Using full set of examples from nightly build: rerun.io/viewer
• The PR title and labels are set such as to maximize their usefulness for the next release's CHANGELOG
• If applicable, add a new check to the release checklist!
• If have noted any breaking changes to the log API in CHANGELOG.md and the migration guide

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To run all checks from main, comment on the PR with @rerun-bot full-check.

[teh-cmc]

@rerun-bot full-check

[github-actions]

Started a full build: https://github.com/rerun-io/rerun/actions/runs/10682478883

[teh-cmc]

I'm still leaving that specific part hardcoded, because this is an example not the end-all-be-all CLI query tool.

It does show why using a full blown ComponentColumnDescriptor as pov is a massive pain though. To be improved on later on.

[jleibs]

Makes sense. We'll always need this as a worst-case fallback path, but I can definitely imagine this being replaced with a series of checks that determine whether particular happy-path join operations are applicable with more efficient implementations for those cases.