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feat(server): stats request limits, session override, cost guard and the demand scan (rows-first p36a) - #1033
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…the _handle_widget_change split (rows-first s1) A default-tier XorqBuckarooWidget and BuckarooWidget publish df_data_dict, then df_display_args, then the rest of the widget_args_tuple observers on a search change, and merged_sd carries the full stat set. These pass on main and pin the behaviour the split must keep. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…(rows-first p31) New tests/unit/server/test_stats_policy.py for buckaroo/server/stats_policy.py, which does not exist yet: - resolve_stats_policy: a table of (backend, source_kind, rows, cols, host_tier) against (tier_target, auto_request, requestable, reason), including the boundaries of each threshold and the three tallyman entries over 70 s. - The ceiling holds for host_tier="full", for a reload that re-resolves against a larger row count, and for a force request, and every tier a result lists as requestable is one a force would be granted. - Probes add no data query: the parquet footer probe reads a small share of a counting file object and decodes no row group, the dtype probe never collects a LazyFrame or executes a xorq expression, and a known xorq count is an input. - route_polars_entry returns "xorq" above R and "eager" at or below it. - Threshold overrides from BUCKAROO_* environment variables. Nothing imports the module yet. The tests error at fixture setup on the missing module until the implementation lands. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
… p31) New buckaroo/server/stats_policy.py, pure and imported by nothing yet: - resolve_stats_policy(backend, source_kind, rows, cols, bytes, host_tier, limits) returns tier_target, auto_request, requestable, reason and estimate over the tiers schema < scalar < full. A ceiling is computed inside the function, so every caller gets the lower of the requested and ceiling tiers with reason "ceiling". A host tier lowers freely and raises only to the ceiling. Eager pandas and polars resolve to full. - route_polars_entry(rows, cols) returns "xorq" above R rows and "eager" at or below it. - probe_dtypes reads a schema without collecting or executing anything, and probe_parquet_rows reads a parquet footer's num_rows without decoding data. A xorq count is an input to the policy, never computed by it. - The thresholds are provisional constants gathered in StatsLimits, each with a BUCKAROO_* environment override read on every call. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…-handler fields (rows-first s1) A schema-tier XorqServerDataflow should match full stats on pinned_rows, data_key, summary_stats_key and (except the stats-derived minWidth) column_config, issue no data query besides the cached count, and keep init_sd hints and sorted windows working. A pending state must write nothing under a full-tier cache key, and a later full assignment must reach merged_sd for the raw, clean and filt scopes. assemble_merged_sd must equal merged_sd, and _handle_widget_change must be built from separately callable all_stats and display-args builders. /load_expr and /reload_expr accept stats_tier and stats_delivery, replay them on reload, and keep them out of the warm short-circuit's has_config tuple. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
… s1)
Add a dataflow-level stats_tier ("full" default, "schema"). The xorq schema
tier builds identity and typing for every column from the expression's
schema, with no data query beyond the cached row count, so a dataflow
constructs in milliseconds rather than the stats' hundreds.
The tier is part of _scope_cache_key, so a schema entry is never read as a
full one, and _populate_sd_cache stores summary_sd under the filt key only
if it was computed for the current frame, klass list and tier. add_analysis
no longer builds DFStatsClass outside the hook when the tier is not full.
The merged_sd observer body is extracted as the pure assemble_merged_sd,
and _handle_widget_change is split into _build_df_data_dict and
_build_df_display_args.
/load_expr and /reload_expr accept stats_tier and stats_delivery, stored on
the session beside dataflow_kwargs and replayed on reload. They stay out of
the has_config tuple; the warm short-circuit compares the stored pair.
stats_delivery="deferred" builds the schema-tier dataflow and publishes it.
Defaults (full, inline) leave behaviour unchanged.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…esolve_stats_policy (rows-first p31) bytes and source_kind were documented as validated but are not: bytes=-1, 'lots', 1.5 and object() are accepted, a np.int64 is echoed unchanged so json.dumps of the result fails, a host tier passed positionally lands in the bytes slot, and source_kind=None or 5 is accepted. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…ation test (rows-first s1) The Max Versions jobs resolve pandas 3, which reports a string column's dtype as 'str' where pandas 2 says 'object'. The characterization test asserted 'object'. Verified in a Max Versions environment (pandas 3.0.6, polars 1.44.2, xorq 0.4.5): the unit suite passes. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…rows-first p31) bytes goes through the same integer check as rows and cols, so a negative, float or non-numeric value raises, a numpy integer is echoed as a plain int and the result stays JSON-serialisable, and a host tier passed positionally into the bytes slot raises instead of being echoed. source_kind must be a str; its vocabulary stays open for the callers that will read it. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…g on a skipped column (rows-first s1) A column in skip_stat_columns gets only name, dtype and length from the full-tier pipeline, so its _type comes from init_sd. The schema tier layers the schema-derived _type and is_* keys over it, so an int64 column that init_sd types as float merges as integer and renders with zero fraction digits instead of the float displayer init_sd asked for. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…ows-first s1) _get_schema_sd never read skip_stat_columns, so a skipped column's schema-derived _type and is_* keys overrode init_sd's _type once merged. The full tier gives a skipped column only name, dtype and length. The schema tier now does the same, so init_sd's _type decides the displayer at both tiers. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…er (rows-first s2) ServerDataflow and PolarsServerDataflow with stats_tier="schema" should publish the display state full stats give (column_config without stats-derived keys, pinned_rows including a host-supplied one, data_key, summary_stats_key) with no stat computed on the data, still apply init_sd, serve sorted windows, take a later full assignment into merged_sd for every scope, and assemble to the same sd as merged_sd. Both backends run through the same parametrized class, plus a pandas test that pins how an object column is typed from its dtype. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
ServerDataflow and PolarsServerDataflow now implement the _get_schema_sd hook,
so stats_tier="schema" builds a dataflow that types every column from its dtype
and runs no stat on the data. schema_sd (stat_pipeline.py) builds the sd the way
process_df shapes it: an empty frame gives {}, a skipped column keeps only its
names. pandas applies the existing typing_stats to a zero-row slice and derives
_type through the _type stat; polars factors pl_dtype_typing out of
pl_typing_stats and feeds it the dtype.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…s (rows-first p31b) The boundary tables now run on the module defaults and are written against the phase-0 proposals: full auto up to 12M rows and 520M cells, scalar auto up to 1.0B cells, full refused above 25M rows or 1.0B cells (force included), a scalar ceiling of 4.0B cells, and polars routed to xorq above 8M rows. Each threshold has an equal, a one-below and a one-above row, in rows and in cells. New tests pin each default to its literal value and cover the two new environment overrides, BUCKAROO_STATS_FULL_AUTO_CELLS and BUCKAROO_STATS_CEILING_FULL_CELLS. They fail on the current constants (10M rows, 500M cells, 50M-row ceiling, no scalar ceiling, R of 10M) and on the missing full_auto_cells and ceiling_full_cells fields. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…tats_request (rows-first s3)
On a deferred /load_expr session a stats_request {stats_gen, scope} should
return a stats_update with the matching stats_gen whose inline wide payload
equals the all_stats an inline session sends, a stale stats_gen should get
stats_aborted and run no query, and /load_expr and /reload_expr should bump the
generation. df_meta.stats should be injected on every frame and survive a
dataflow-field change, which returns the session to the schema tier. With a
caps client and a legacy client on one session, the legacy client should keep
getting complete messages through the websocket broadcast, the /load_expr,
/reload_expr, /load and /load_compare pushes and the highlight overlay, while
the caps client gets a stats-free frame and then pulls a stats_update. A spy
telemetry sink should see a stats.request span.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…measurements (rows-first p31b) Full auto now needs at most 12M rows and 520M cells (was 10M rows), scalar auto goes to a 1.0B cell budget (was 500M), `full` is refused above 25M rows or 1.0B cells including for a forced request (was 50M rows), scalar gets a 4.0B cell ceiling by default (was unset; an extrapolation with no measurement behind it), and polars routes to xorq above 8M rows (was 10M; the figure assumes pre_limit False). Each DEFAULT_* constant carries the measurement it comes from. The two new bounds are full_auto_cells and ceiling_full_cells, appended to StatsLimits, with BUCKAROO_STATS_FULL_AUTO_CELLS and BUCKAROO_STATS_CEILING_FULL_CELLS as overrides under the same parsing rules. _size_tier and _ceiling_tier read them; signatures and the result shape are unchanged. Three existing tests that hard-coded the old boundaries are updated: the numpy-integer case (11M rows is now full), the reload case (a 40M-row entry is now refused full) and the empty-environment case for the scalar ceiling (an empty value now means the 4.0B default, not no ceiling). Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…eration edge cases (rows-first s3) Four more cases for the stats wire format, kept in their own commit so each is seen failing on CI before the implementation lands. Returning to a state whose stats were completed once is answered from summary_stats_cache with no query. Completing the stats keeps the session's component_config on the refreshed display config. A warm /load_expr, which rebuilds nothing, leaves stats_gen alone. A stats_request on a session with no data is answered with stats_aborted. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…ed sessions (rows-first s3)
A client that advertises ?caps=stats_update gets a stats-free initial_state on a
deferred /load_expr session (df_meta.stats.status "pending") and pulls the stats
with stats_request {stats_gen, scope}. The reply is a stats_update carrying the
dataflow's all_stats as an inline wide envelope, or stats_aborted when the
generation is stale. The request is the whole run: one synchronous call that
computes the full stats, writes the full-tier summary_stats_cache entry, assigns
summary_sd and refreshes the session snapshot through one helper.
stats_gen is a server-owned counter bumped by every load handler and by a state
change that touches a dataflow field, which also returns a deferred session to
the schema tier. df_meta.stats is injected by build_state_message from the
session, since the dataflow rebuilds df_meta wholesale. Every send site goes
through build_state_message_for, so a client without the capability still gets
complete messages (its missing stats run synchronously first); broadcast_state
replaces the five copies of the send loop and sends to capable clients first.
The stats_request branch binds the session's telemetry sink and emits a
stats.request span.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…s (rows-first s4) Both pass on the current code. process_df is written out as the process_column loop it is, and each xorq histogram query's snapshot-cache key is compared with the key of a query built in the test, so the refactor into resumable units that follows can be checked against something that does not go through the units. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…tore (rows-first s4) Each stats class gets plan(state) and run(unit, acc): the fragments of the planned units, assembled through assemble_merged_sd, must equal the full-stats merged_sd on pandas, polars and xorq with init_sd, cleaning and overrides; a column group returns only its columns; skip_stat_columns columns get no unit; the xorq batch can be split by column chunk behind a default-off flag and is refused for anything but a plain parquet scan; the histogram cache keys stay put. A StatRun held on the session, keyed by (stats_gen, scope), keeps an append-only fragment list and accumulator, runs a unit only when asked, is dropped when stats_gen changes, and each connection keeps its own cursor. test_the_batch_is_one_query_by_default passes on the current code: it pins the default the flag must not change. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
StatPipeline and XorqStatPipeline get plan(state), new_accumulator(state) and run(unit, acc); process_df and process_table are those three in order, so the inline path and a caller running units one at a time compute the same stats. pandas and polars plan one unit per non-skipped column. xorq plans the scalar batch (which also yields histogram_bins), then one histogram query per column, visible columns first. The batch can be cut into column chunks sized by cells when a host sets stat_chunk_cells, and only for a plain parquet scan: any other source falls back to the single batch and logs why. A StatRun, kept on the session by (stats_gen, scope), holds the planned units, an append-only fragment list and the accumulator. It has no thread, timer or callback, begin_stats_generation drops it, and each WebSocket connection keeps its own StatCursor into the list. CustomizableDataflow.build_stats is the one place a stats class is built, with run=False for plan/run callers. Two of the new tests are corrected here: the default-path test now ignores the PERVERSE_DF self-check units, and the xorq comparisons round floats to nine digits because a parallel aggregate adds its partial sums in varying order. The new-module imports in the tests move to module level. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
… once (rows-first s4)
A column group, the priority columns and StatRun's prefer hint accept
original or rewritten (a, b, c) names and read each name in both. When an
original name equals another column's rewritten name, a group returns the
columns of both, priority ranks both first, and prefer picks the unit of
whichever comes first in the frame.
On a frame whose columns are c, b, a (rewritten a, b, c):
- StatState(df, columns=('c',)) plans the units of c and a.
- priority=('a',) plans c before a.
- StatRun.next_unit(prefer=('a',)) picks the unit of c.
The new tests also pin the namespace argument the fix adds, so a client that
holds the rewritten names can ask for exactly those: StatState(namespace=)
and StatRun.next_unit/run_next(namespace=), with "any" (the default),
"original" and "rewritten".
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…rst s4) A column group, StatState.priority and StatRun's prefer hint matched a name against both the original and the rewritten (a, b, c) column names. When an original name equals another column's rewritten name, one name picked two columns: a group returned columns that were not asked for, and prefer ran the unit of whichever column came first in the frame. resolve_names reads each name once. In "any", the default and what the code did for names that do not collide, a name that is an original column name picks that column and only a name that is not one is read as a rewritten name. StatState(namespace=) and StatRun.next_unit/run_next(namespace=) also take "original" and "rewritten", so a caller that holds the client's rewritten names says so and gets exactly those columns. Priority and prefer names are resolved against every column of the frame, not only the columns in the group, so a name picks the same column whatever group is asked for. prioritized now takes the state, since it needs the frame's columns and the namespace to read the priority names. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…t cursors and the final assignment (rows-first s5) Covers the request branch that runs units for a time budget (at least one, one cold unit per budget), the per-handler cursors over a shared StatRun, the final assignment that frees the run and carries the rebuilt df_display_args, a legacy client finishing a run in progress, a concurrent infinite_request between units, the end-to-end order of first initial_state, rows and stats, /reload_expr mid-run, and the stats.unit and firstpull.stats_total spans. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…nt cursors and the final assignment (rows-first s5) A stats_request with incremental: true runs the units of the session's StatRun for about STATS_BUDGET_S (at least one) and answers with the fragments the asking client has not seen, read through the handler's own StatCursor. The request that runs the last unit does the final assignment in complete_stats: the full-tier summary_stats_cache entry, summary_sd, the session snapshot and the status in one step, the run freed, and the final reply carries the rebuilt df_display_args when its digest differs from the one the client holds. Without the field a request is still the whole run, now finishing the run's remaining units when a client has made progress. A legacy client's complete frame does the same. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…handlers (rows-first p33) stats_tier takes auto, full, scalar or schema on /load_expr and /reload_expr and is stored with the pair. The policy resolves after the schema-tier dataflow and the count exist, is stored on the session, is reported in df_meta.stats (tier_target, reason, auto_request, requestable, estimate, omitted_keys, approx_keys, demand_columns, each with its documented default) and is applied at WebSocket open only for a client that sends ?caps=stats_update,stats_ondemand. The version-skew cases (no caps, stats_update only, both bits, an old server) and /load, which keeps resolving to full, are covered. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…and the compare reset under a stats policy (rows-first p33) Cases found untested after the first tests commit, each one a regression the first set did not catch: a stats_update client pulling units from a policy session gets full-tier updates and the final reply carries the rebuilt df_display_args, a scalar tier named with inline delivery builds a schema dataflow, and /load_compare clears the policy a session held. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…irst p33) /load_expr and /reload_expr accept stats_tier auto, full, scalar or schema, stored with the pair and kept out of has_config, so the warm short-circuit holds. When the dataflow is built at the schema tier the handler resolves the policy (resolve_stats_policy) from the count it already has, stores it on the session and starts the stats generation from it: a target below full is not_computed with the policy's reason. df_meta.stats reports the policy as tier_target and estimate, plus auto_request, requestable, omitted_keys, approx_keys and demand_columns where they differ from their documented defaults. It is applied at WebSocket open only for a client that sends ?caps=stats_update,stats_ondemand. A client with stats_update only is told the session is pending and pulls the stats, and a client with no caps gets them at connect, as for any deferred session. A tier the host named (scalar, schema) reaches every client as before. A session on an explicit stats_tier full within the ceiling sends the message it always has. /load keeps resolving to full: it does not read the field and clears a policy left on the session. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
… p34) A xorq stat run at the scalar tier is the scalar class of the batch without approx_median and distinct_count, and no histogram query. Its histogram_bins come from the batch's min and max. The run behaves like a filtered one: fragments go to the clients and nothing is assigned to the dataflow, the session snapshot or summary_stats_cache, so scalar stats are never served as the complete ones. Tests cover the plan, the queries a scalar run issues, the fragment union against the full stats, the bins, the chunked batch, the StatRun key and assignment rule, which clients are served the tier, and the stats_update messages of an ondemand client on a scalar target. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…d generations (rows-first p34) A deliberate regression of the implementation showed four behaviours the first set of tests does not cover: a stat that reads a key the scalar tier leaves out is left out with it, a stat that reads distinct_count runs on the unknown, a scalar request emits the request and unit spans with the scalar tier and no completion span, and a dataflow-field change drops the scalar run and starts one over the new state. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…signed (rows-first p34) StatState takes a tier. A xorq run at the scalar tier is the batch alone, in the same column chunks, without the aggregates behind median and distinct_count and with no histogram unit. Its histogram_bins come out of the batch's min and max, so color_map needs no histogram query. The accumulator withholds median, distinct_count, distinct_per and histogram, so no fragment and no assembled sd carries a key the tier did not compute. The pandas and polars pipelines refuse a non-full state. StatRun takes a state, and reports its tier and whether it assigns (only the full tier over every column does). The full run keeps its (stats_gen, scope) key; every other run has a key of its own, so it never takes the full run's place. start_stat_run takes a tier and a column group. _run_summary refuses a run that does not assign, so a scalar or column-scoped sd is never written to summary_stats_cache as the complete one. A stats_request from a client that advertised stats_update and stats_ondemand, on a session whose policy target is scalar and has nothing computed, runs the scalar units and answers stats_update with tier scalar, final and remaining. The run behaves like a filtered one: the fragments go to the clients that ask (each through its own cursor) and nothing is assigned to the dataflow, the session snapshot, summary_stats_cache or the status. Other clients are served as before. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…demand scan (rows-first p36a) A stats_request from a client that advertised both capability bits can now say tier, force and columns. The tests pin what the server does with them: the ceiling refuses a tier for the cells asked for and runs nothing, requestable and the target decide which tier a whole-table request may name, force raises the target through a session override that survives a dataflow-field change for the unfiltered scope only, an automatic unit over the budget pauses the session (not_computed for cost) until a force request, and the pause survives a generation and /reload_expr. The demand scan reads the color_map rules of the built config (overrides and rules a klass adds at style time) with no query, and a scoped request computes those columns only. Every test here fails on the earlier code. The guard tests that pass there (a client without both bits is served as before, a session with no policy ignores the fields) go in with the implementation. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
📦 TestPyPI package publishedpip install --index-strategy unsafe-best-match --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ buckaroo==0.15.9.dev37240210873or with uv: uv pip install --index-strategy unsafe-best-match --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ buckaroo==0.15.9.dev37240210873MCP server for Claude Codeclaude mcp add buckaroo-table -- uvx --from "buckaroo[mcp]==0.15.9.dev37240210873" --index-strategy unsafe-best-match --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ buckaroo-table📖 Docs preview🎨 Storybook preview |
…the demand scan (rows-first p36a) A stats_request from a client that advertised both capability bits reads tier, force and, with a tier, columns. The server judges it: the ceiling for the cells asked for (resolve_stats_policy with the tier as the host's) answers a refusal and runs nothing, a whole-table tier must be the target or above it with force, and a paused session refuses a request that is not forced. A force above the target stores stats_override on the session, and effective_stats_policy raises the target for the unfiltered scope and for the generation it was forced in. begin_stats_generation, stats_meta and serves_scalar_tier read the effective policy. An automatic request that ran a unit over STATS_COST_BUDGET_S and left units to run sets cost_paused, which begin_stats_generation reads, so the pause survives a stats_gen bump and /reload_expr until a force request. The override and the pause are forgotten by /load, /load_compare, another expression and a body that names a tier. stats_policy.demand_columns scans the built display config for color_map rules and names the columns they read; the snapshot refresh writes them to stats_policy["demand_columns"] for a schema target, and a scoped request computes those columns only, with a run that is never assigned. The final reply of a run that does not assign now carries the session's status. Guard tests that pass on the earlier code go in with this commit, and the elapsed_ms test has wider margins on both sides. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…n it continues after a cost pause (rows-first p36a) A client that continues a cost-paused session (force with no tier, or a tier equal to the target) never has its display_args_hash recorded, so the final stats_update carries no df_display_args and the client keeps the config its not_computed frame carried. Two clients are in that state: one that connected while the session was paused, and one that changed state (a search) while it was. Both complete the session with force and expect the rebuilt config in the final reply. The client that connected pending before the pause is covered by the existing tests. Both tests fail on the earlier code: the final reply has no df_display_args. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
…sed run (rows-first p36a) _apply_force recorded the client's display_args_hash only when a force raised the target above the policy's. A continue after a cost pause names no tier, or the target, so the digest was never recorded: build_state_message_for had already cleared it for the paused not_computed frame, and the final stats_update left out df_display_args. A client that connected while the session was paused, or changed state while it was, kept the schema-tier config its frame carried after the session completed. The digest is now recorded for any whole-table force that runs the full tier, by raising the target or by continuing to it. A force for the scalar tier or for named columns still records none, since neither run ends in an assignment. A client that already holds a digest keeps it. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
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Review pass on this PR: one finding, confirmed and fixed. Finding (medium): a Continue after a cost pause never records the client's display digest. I reproduced both cases before changing anything. In each, the final reply had no How it was addressed
Every check on 909ed59 is complete and green (the deploy job is skipped), and the local unit suite is 2058 passed. No existing test was changed. Not covered: the digest is taken when the client sends |
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Closing. The cost guard pauses between units and the demand columns are served as scoped These still apply to an explicit |
…count memo (rows-first p37) stats_policy gains GuardLimits (BUCKAROO_SORT_DISABLE_ROWS, default 25M rows; BUCKAROO_SEARCH_DISABLE_ROWS, default none) and resolve_source_guards, apart from the stats thresholds. A session a host opened with a stats policy resolves them at /load_expr and /reload_expr from the count load took. Above the sort threshold the xorq dataflow finishes its display config with disable_sorting, so no klass or override leaves a sortable column in a display infinite_request serves, and a sorted infinite_request is refused with error_code sort_disabled before any query runs. df_meta carries sort and search when one is disabled. handle_infinite_request_xorq holds the searched expression per (base expression, term), so the second window of a search is a hit in _expr_count's cache and issues no count. Rebased onto #1029 without the closed #1031 and #1033: the guard resets no longer call reset_stats_controls, session_dataflow stays in stats_wire, and the wire tests share a _LimitsWire base ported from #1033 without its unit and cost helpers. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
Stacked on #1031 (
feat/rowsfirst-p34-scalar-tier-units), which carries #1021, #1022, #1024, #1026, #1028, #1029 and the stats policy of #1019 and #1023. This PR is based onmainso the repo's Checks workflow runs on it (itspull_requesttrigger usesbranches: "*", which does not match a base branch containing a slash). The diff therefore includes the commits of those PRs until they merge. The commits of this phase ared4477c46(failing tests) and9af4042c(implementation); read only those (git diff origin/feat/rowsfirst-p34-scalar-tier-units...HEAD).Problem
A client that advertised
stats_ondemandcan be told a session has no stats (not_computed) and what it could ask for (requestable), but it cannot ask. Astats_requestcarries no tier, so the only runs a server can start are the ones the policy target names, and a request for anything else isnot_requestable. Three things the plan puts on the server are missing:requestableare advertised but not enforced on a request, so a client that sends a tier the policy did not offer has nothing stopping it.stats_genbump or/reload_expr.histogram_binsof itsval_column. When the policy computes no stats, those columns get no bins, and nothing finds out which columns they are.Phase and plan references
Rows-first p36a, from
buckaroo2-reports/plans/: plan 3 (03-no-summary-stats-for-large-files.md) section 6 "Phase 6a", with section 3.2 (the cost guard,elapsed_ms), section 3.3 (the demand-driven minimum) and section 3.4 (the control's server side:force, the ceiling answer, the session override). Plan 1 sections 3 and 4.0, plan 2 sections 3 and 4.1.Approach
stats_requestreadstier(scalarorfull),force(a boolean) and, together with atier,columns(the grid'sa, b, cnames) that scope the run to those columns. Without atier,columnsis only the ordering hint it was. A value the server cannot read isstats_abortedwith reasonbad_request. Every other client, and a session with no policy, ignores all three fields._gate_request), in this order. The ceiling:resolve_stats_policyis called with the requested tier as the host's, over the cells asked for (all of them, or rows times the named columns), so the ceiling is the same function load uses; a tier it lowers is answeredstats_update {final: true, status: "not_computed", reason: "ceiling"}with no payload and nothing run. Then, for a whole-table request, the tier must be the target or above it withforce(below the target, or above it withoutforce, isnot_requestable, as is a schema target with no tier). Then the cost pause: a request withoutforceon a paused session is answered with reasoncost. A column-scoped request needs noforce, since it is how the demand columns are asked for.forceabove the target storesstats_overrideand the generation it was made in on the session.effective_stats_policy(session)is the policy in force: the one resolved at load, or the one the override tier resolves to for the same entry (never lower than the target, still under the ceiling, thresholds read again). It applies to an unfiltered state and to the generation it was forced in. "Filtered" is a quick command (a search) on the operations, which is the difference between the dataflow'sfiltandcleanchains; a cleaning method or a post-processor does not make a state filtered.begin_stats_generation,stats_metaandserves_scalar_tierread the effective policy, so a forcedfullmakes the sessionpendingforfullagain after a dataflow-field change, and a client that connects later is told so.run_unitscan report how long each unit took (from the run's own timer). An automatic request, which is a request withoutforce, that ran a unit overSTATS_COST_BUDGET_Sand whose reply leaves units to run setscost_pausedand the statusnot_computedforcost. A unit cannot be cut short, so the unit that went over has run; the guard stops the next one. A request that finishes the run pauses nothing, and a forced request never pauses. Aforceclears the pause, and the run continues where it stopped (ranis kept). The pause is on the session, sobegin_stats_generationreads it (initial_stats_status(..., cost_paused)) and it survives astats_genbump and/reload_expr. A client without both bits is not held by it: it is toldpendingand gets the stats when it pulls, as before.reset_stats_controlsclears the override and the pause on/load,/load_compare, a/load_exprof another expression, and a/load_expror/reload_exprwhose body names astats_tier. A rebuild of the same expression, or a reload that names none, keeps them.stats_policy.demand_columns(display_args, pairs)collects theval_columnof everycolor_map_configwhosecolor_ruleiscolor_map, in any display, and returns the rewritten names in the table's order. It reads the built config, so it covers rules in the column overrides and rules a klass adds at style time, and it sends no query. Aval_columnmay be the rewritten name or an original one (a rewritten name wins), and one that names no column is dropped. A categorical rule, a tooltip and acolor_mapwith noval_columncreate no demand.refresh_demand_columnswrites the result tosession.stats_policy["demand_columns"]at load and with every snapshot refresh (a dataflow-field change,/reload_expr), for aschematarget only, since a higher target computes those columns anyway;df_meta.statsreports it to an ondemand client through the existing_policy_fields._serve_runfromstart_stat_run(tier=..., columns=...), the run p34 added: its key is(stats_gen, scope, tier, columns), two requests for the same columns in any order share it, it never assigns, and a client that asks later reads its fragments with no query. Its final reply says what the session still is (status, andreasonwhen there is one). The scalar run of p34 is served by the same function and now says the same on its final reply.What changes
buckaroo/server/session.py:stats_override,stats_override_genandcost_pausedonSessionState;initial_stats_status(..., cost_paused);effective_stats_policy,reset_stats_controls,restore_stats_status;begin_stats_generationandstats_metaread the effective policy;session_dataflowmoved here fromstats_wire(still importable from there).buckaroo/server/stats_wire.py:STATS_COST_BUDGET_S,REQUEST_TIERS,TierRequest,_tier_request,_gate_request,_apply_force,_pause_if_slow,_refused;_serve_scalaris now_serve_run(tier and columns);run_units(timings=);refresh_demand_columns, called fromrefresh_session_snapshot;serves_scalar_tierreads the effective policy.buckaroo/server/stats_policy.py:demand_columns; the module docstring no longer says nothing imports it.buckaroo/server/handlers.py: the resets above,same_expressionat/load_expr, the demand scan after the snapshot is stored.websocket_handler.py,dataflow.pyor any client.Tests
Two commits:
d4477c46(failing tests, pushed alone) and9af4042c(implementation and guard tests). Tests are in the existing files of their kind.test_stats_policy.py(pure, every Python and Windows):TestRequestsOverTheCeiling,TestMalformedTierRequests,TestRequestableTiers,TestCostPausedStatus,TestEffectiveStatsPolicy,TestDemandColumns. They cover the ceiling answer for six combinations of host tier, limits and request, each unreadable field, which tiers a whole-table request may name, the status a paused session starts a generation with and the order of the checks, what a forced tier raises the policy to and where it applies, and the demand scan on every shape of config.test_load_expr.py(xorq, over HTTP and WebSocket):TestForcedRequestsWire,TestCostGuardWire,TestCostGuardUnits,TestDemandScanWire,TestTierFieldsAndOlderClients. A forced scalar and a forced full run for real; the ceiling answer runs no query; the override across a field change, a search, a reload and a new expression; the pause across a generation, a reconnect and a reload; a unit under the budget, a forced unit and a request that finishes the run do not pause;elapsed_mson updates and refusals; the demand columns of a klass at style time, of an override, and none for categorical rules, with zero stat queries at load; a demand request runs the named columns only, assigns nothing and is replayed to a second client with no query; the ceiling judged per named column.stats_update-only client has the fields ignored and a host-named schema target still refuses it, a session with no policy ignores them, an explicitfullsession serves plain requests as before, a client without both bits is not held by a pause, a session that computes the columns anyway has no demand, categorical rules alone have none, a session nobody forced staysnot_computedthrough a field change, a scoped request on a complete session is answered from the dataflow).The
elapsed_mstest has bounds of 50 ms ind4477c46: a request that ran a 50 ms query takes at least that long, and a refusal takes less.9af4042cwidens both sides (a 300 ms query, bounds of 250 ms), because an upper bound of 50 ms on a refusal can fail on a loaded machine (the load average here reached 35 during the full suite). The test fails on the earlier code for the same reason in both versions: the scoped request is refused withnot_requestable.On
d4477c46all ninePython / Testjobs failed (3.11 to 3.14, Max Versions 3.11 to 3.14, Windows), with all 28 checks completed; the other 18 succeeded (Docs, Lint, Typecheck, the JS job, the wheel build and the Playwright jobs among them) anddeploywas skipped. CI logs were not read (the REST log API is rate-limited for this account), so the reasons rest on the local run of the same commit: 107 of the new tests fail, each on a missing session attribute or function, on a reply with notier,finalorelapsed_mswhere astats_updateis expected, or on a request refused withnot_requestableorstats_abortedwhere an answer is expected, and the other 1940 unit tests pass.CI on
9af4042c: all 28 checks completed, 27 succeeded (one of them the Read the Docs status) anddeploywas skipped. That includes all ninePython / Testjobs,Python / Lint,Python / Typecheck,Docs / Build + Check Links, the JS job, the wheel build and the Playwright jobs.Local checks on
9af4042c:pytest ./tests/unit -m "not slow") gives 2056 passed and 5 skipped: the 1940 of feat(stats): xorq scalar tier units, served as fragments and never assigned (rows-first p34) #1031, the 107 failing tests, and the 9 guard tests. The same 2056 and 5 in an environment resolved the way the Max Versions job does it (pandas 3.0.6, polars 1.44.2, xorq 0.4.5, numpy 2.5.3), in a copy of the tree with the lockfile removed anduv sync --resolution=highest. That copy left outpackages/, so one test that reads a committed JS fixture (test_xorq_window_fixture.py) failed there until the fixture file was copied in; it then passed._gate_requestremoved, the pause never set, set on a final reply, set on a forced request, never cleared byforce, the override not recorded, ignoring the filtered scope or lasting only one generation, the reset removed from each of its triggers, the demand scan not refreshed, not limited to aschematarget, including categorical rules, letting an original name win, the fields applying to every client or to a session with no policy, a scoped request served as the whole run, and others). On the first set of tests 40 were killed and five survived. One survivor was an equivalent mutation of a redundant check, which is gone now (simplifying it also exposed that an unhashableval_columnraisedTypeErrorin the scan, which is fixed and tested). The other four led to two new tests (a pausedschematarget has nothing to request;/loadand/load_compareforget the controls) and two tighter ones (a forced unit is checked right after its reply, not after a later forced request has cleared the pause; a session with no policy ignores unreadable fields too). With those, all the others are killed.python -m buckaroo.server --no-browser, started and stopped by me, killed by listener PID, ports free afterwards), on a 60,000-row, three-column xorq build with a deferredautosession. On port 8941 withBUCKAROO_STATS_FULL_AUTO_ROWS=1000,BUCKAROO_STATS_SCALAR_AUTO_CELLS=100000andBUCKAROO_STATS_CEILING_FULL_ROWS=50000and acolor_mapoverride namingprice: the first frame of a client with both bits wasnot_computed, reasonsize,tier_targetschema,requestable["scalar"]anddemand_columns["a"]. A request with no tier wasnot_requestable; the demand request (tier: "scalar",columns: ["a"]) was astats_updatewith the scalar rows of columnaonly in 16.3 ms; a bad tier wasbad_request;scalarwithoutforcewasnot_requestable;fullwithforceand a scopedfullover three columns were refused with reasonceilingin 0.0 and 0.1 ms;scalarwithforceran for all three columns (24.3 ms) and a client that connected afterwards was toldtier_target: "scalar". Astats_update-only client was toldpendingand a no-caps client got the complete stats. On port 8942 with the cost budget set to 0 and one unit per request by a small launcher script (a 10 s unit cannot be produced on this table): the first automatic request returned a partial update and paused the session; a client that connected then was toldnot_computed, reasoncost,tier_targetfull, while astats_update-only client was toldpending; the next automatic request was refused with reasoncost; aforcerequest continued the run where it stopped and the last one wasfinal.Why default behaviour is unchanged
tier_fields_apply: a client that sent bothstats_updateandstats_ondemand, on a session that has a policy. No released client sendsstats_ondemand, and a session has a policy only when it is deferred or a host namedscalarorschema.stats_overrideorcost_pausedwithout them, sobegin_stats_generation,stats_metaandserves_scalar_tierreturn what they returned.df_meta.statschanges only for an ondemand client of aschematarget whose config has acolor_maprule (demand_columns), of a forced session (the effective target) and of a paused one.fullispendingwhatever its delivery. That case could not occur before this PR, since a policy exists only for a dataflow built at the schema tier and a host namingfullthere is the explicit-fullcase feat(server): stats policy wire contract and handler plumbing (rows-first p33) #1029 pins.test_stats_policy.py.Deviations from the plan
STATS_COST_BUDGET_Sis 10 s, a module constant and not an environment setting. The plan gives no number; this is the tallyman client's base timeout and is marked provisional beside the constant with the measurements it can be compared with.force, and a later automatic request can pause again.cleanchain, which survives a filter flip, so it does not end the override. A force made in a filtered state serves that state and does not reach another filtered one.forceabove the target sets the override; aforcethat only continues the target (a "Continue" after a pause) sets nothing. A force with no tier on a schema target isnot_requestableand clears nothing.estimate). Named columns are judged by rows times their number, so a ceiling that refuses the whole table can still allow a few columns.stats_updatewithtierset to the tier asked for (the target when none was named),status: "not_computed"always, and no payload ordf_display_args.statusandreason. p34's scalar final reply carried neither; no existing test pinned that.df_meta.statsreportstier_target,estimateand the other policy fields for an explicitfullsession while it is paused, which it does not otherwise (feat(server): stats policy wire contract and handler plumbing (rows-first p33) #1029). A client that readsreason: "cost"needs to know which tier aforcecontinues.demand_columnsto the session policy (the p33 interface note). It is empty unless the target isschema. Nothing on the server requests the demand columns: they are a scopedstats_request, which the client sends (phase 5), under the same ceiling and pause.reset_stats_controlsand its triggers are mine; the plan says only that the override and the pause survive a generation and a reload.session_dataflowmoved fromstats_wiretosession, because the effective policy needs it andstats_wireimportssession.Not in this PR
demand_columnsand thecoststate (phase 5); sort and search guards (phase 7); the config upgrade after stats complete (phase 6b); default flips (phase 9).STATS_COST_BUDGET_S.StatRun(an accumulator and its fragments, no data) until the generation changes; a client that asks for many different groups grows that dict.stats_updateholds schema rows only).🤖 Generated with Claude Code