Option to disable Physical input schema should be the same as the one converted from logical schema error

@jayzhan211

Is your feature request related to a problem or challenge?

This bug, released in DataFusion 42.0.0 ,

Fix the schema mismatch between logical and physical for aggregate function, add AggregateUDFImpl::is_null #11989

Added a new check in the DefaultPhysicalPlanner that the schema of the output plan is the same as the input plan

datafusion/datafusion/core/src/physical_planner.rs

Lines 660 to 662 in 818ce3f

    
           if physical_input_schema != physical_input_schema_from_logical { 
        
               return internal_err!("Physical input schema should be the same as the one converted from logical input schema."); 
        
           }

While @jayzhan211 's heroic efforts has this passing in all the DataFusion tests, it turned out this check failed on many downstream implementations:

[EPIC] Schema metadata handling / bugs #12733 lists issues we hit during our upgrade in InfluxDB 3.0
chore: upgrade to datafusion 43 delta-io/delta-rs#2886 @ion-elgreco and @rtyler and @Xuanwo while updating delta.rs to DataFusion 42.0.0

Downstream in InfluxDB 3.0 we turned the check into a warning in our fork to unblock our upgrade

We even made a patch release to try and get the delta-rs upgrade working:

Release DataFusion 42.1.0 #12813

But it is still failing when I write this (see delta-io/delta-rs#2886 (comment))

Internal error: Failed due to a difference in schemas, original schema: DFSchema { inner: Schema { fields: [Field { name: "id", data_type: Utf8, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "price", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "sold", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "price_float", data_type: Float64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "items_in_bucket", data_type: List(Field { name: "element", data_type: Utf8, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "deleted", data_type: Boolean, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "__delta_rs_update_predicate", data_type: Boolean, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }], metadata: {} }, field_qualifiers: [None, Some(Bare { table: "target" }), None, None, None, None, None], functional_dependencies: FunctionalDependencies { deps: [] } }, new schema: DFSchema { inner: Schema { fields: [Field { name: "id", data_type: Utf8, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "price", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "sold", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "price_float", data_type: Float64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "items_in_bucket", data_type: List(Field { name: "item", data_type: Utf8, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "deleted", data_type: Boolean, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "__delta_rs_update_predicate", data_type: Boolean, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }], metadata: {} }, field_qualifiers: [None, Some(Bare { table: "target" }), None, None, None, None, None], functional_dependencies: FunctionalDependencies { deps: [] } }.

Describe the solution you'd like

Note there is at least one open outstanding bug: #13010

I would like some way to disable this check to unblock upgrades in downstream crates.

Describe alternatives you've considered

I propose we add a new config value that lets downstream crates opt in / out of this check, similarly to datafusion.optimizer.skip_failed_rules (see Config Docs)

Something like:

datafusion.execution.validate_schema: If true, the DefaultPhysicalPlanner will error if the input plan's schema does not exactly match the output plan.

Additional context

No response

I should clarify -- ideally this check should be enabled by default and it is a goal we should shoot for.

However, as there are clearly bugs in the code that currently prevent it from passing cleanly in all cases (which were previously in the code), I think it is better to relax the check and sort out the errors rather than hard failing plans.

@alamb

However, as there are clearly bugs in the code that currently prevent it from passing cleanly in all cases (which were previously in the code), I think it is better to relax the check and sort out the errors rather than hard failing plans.

Some additional context -- we have definitely not isolated all the bugs this check uncovered. Even with this know bug (#13010) patched for us, we are still encountering this failed check every few minutes. Changing this check to a warning, not an error, has been necessary for us.

Assuming that we are not the only ones, having the feature @alamb proposed here (to also convert to a warning based on configuration) would help unblock others from ungrading datafusion IMO.

We (InfluxData) will likely contribute fixes back upstream into DataFusion as we find issues as well

It is probably happens when users utilize only physical planner, although there are schema alignments that happening on logical planner?

I remember bunch of issues on schema comparison when different null flag for the column caused a problem.Since DF reworked the Schema methods this issue might come up again

@wiedld

@wiedld are you able to capture failing queries (or rather: queries giving a warning) and maybe turn some into actionable issues for the community?

The question I'd want answered is: does disabling this check hide an actual problem or are we confident the problem exists within the check itself? That is, do we know for certain that disabling the check isn't allowing faulty output? In general I recommend against features to disable checks but I also recognize that unblocking downstream users may be more important.

The question I'd want answered is: does disabling this check hide an actual problem or are we confident the problem exists within the check itself?

I believe disabling the check hides actual problems -- a list of such problems is here #12733

However, those plans ran in DataFusion 41 (and sometimes metadata was dropped from the output schema) and now the plans refuse to run.

So depending on your perspective this is either an improvement or regression:

It is a regression for a user running SQL queries perspective because a query that used to run great no longer does
It is an improvement for a developer as it now makes it easy to find queries that violate invariants

So having a flag to change behaviors based on your point of view I think makes sense

That is, do we know for certain that disabling the check isn't allowing faulty output? In general I recommend against features to disable checks but I also recognize that unblocking downstream users may be more important.

No, we do not know this for certain. I think my point of view is that running with the check disabled is no worse than DataFusion 41 so while not ideal, it isn't worse

@comphead

It is probably happens when users utilize only physical planner, although there are schema alignments that happening on logical planner?

There are two classes of errors we have seen so far in InfluxDB:

Null declarations as predicated by @comphead
Metadata mismatches (metadata is dropped by some physical optimizer)

I believe delta-rs is also seeing field name mismatches (e.g. the embedded fieldname on ListArray is "item" vs "element" or something)

Before DF 41 when doing a schema comparison we relied on helper methods which excludes nullability and metadata comparison. I suppose this method is gone after the refactoring and we need to revive it and use for schema comparison

@wiedld

@wiedld are you able to capture failing queries (or rather: queries giving a warning) and maybe turn some into actionable issues for the community?

@findepi I'll try to get us actionable issues this week. Specifically, I need to isolate reproducers in either our code base (e.g. our physical optimizers) versus datafusion.

@wiedld

I believe disabling the check hides actual problems -- a list of such problems is here #12733

All currently known looks like solved, right? Or am i looking at this the wrong way?

I'll try to get us actionable issues this week

Thank you @wiedld !

@wiedld

I believe disabling the check hides actual problems -- a list of such problems is here #12733

All currently known looks like solved, right? Or am i looking at this the wrong way?

I think it is more accurate to say "all currently filed issues have been resolved"

@wiedld and think we have at least one more issue that is as yet unfiled (that we see occuring in our logs after we upgraded DataFusion and turned this error into a warning). More to come -- we are working on getting a self contained reproducer

@wiedld

All currently known looks like solved, right? Or am i looking at this the wrong way?

I think it is more accurate to say "all currently filed issues have been resolved"

know / filed -- it seems like we mean mostly the same 👍

we are working on getting a self contained reproducer

thanks!
that would be tremendously helpful! and as @wiedld pointed out, would ensure the bug is indeed in DF code.

Anyone willing to help make a PR with this change?

I am making a PR for this

@alamb

I am making a PR for this

Sorry what PR @alamb, I'm a bit lost, is it to fix the schema equality and not rely on nullability/metadata?

@alamb

I am making a PR for this

Sorry what PR @alamb, I'm a bit lost, is it to fix the schema equality and not rely on nullability/metadata?

I think seeing the PR might be easist way to see what I am talking about #13176. It is a relatively small change

Do we have a stable repro case on this for DF only? I'm thinking on fixing the schema equality as it would fix the issue without params

@wiedld

Do we have a stable repro case on this for DF only? I'm thinking on fixing the schema equality as it would fix the issue without params

We have fixed all (known) DF bugs on main. The known ones are listed on #12733 I believe. However @wiedld and I are quite confident there is at least one more (as yet unfiled one) that we are seeing in our production system. Even once we file and fix that I am not at all confident there won't be any others

I view adding this configuration option as an insurance policy

another side of the medal is if there is a critical issue like schema doesn't match because of data/ordering they won't catch it because param enabled and eventually can end up with corrupted data.

My vision we should correctly implement Eq for Schema or provide a method that checks everything but nullability and metadata.

My vision we should correctly implement Eq for Schema or provide a method that checks everything but nullability and metadata.

I think it is somewhat debatable if we should/shouldn't be checking that the nullability and metadata matches. I actually think having the invariant that the corresponding physical plan created for a LogicalPlan should have the exact same schema seems quite reasonable 🤔

@wiedld

@wiedld and think we have at least one more issue that is as yet unfiled (that we see occuring in our logs after we upgraded DataFusion and turned this error into a warning). More to come -- we are working on getting a self contained reproducer

that would be tremendously helpful! and as @wiedld pointed out, would ensure the bug is indeed in DF code.

Thus far we have found 1 additional schema mishandling bug, triggering this check, where the bug was in datafusion. If I encounter more bugs in DF code, I'll add it to the Epic #12733.

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Option to disable `Physical input schema should be the same as the one converted from logical schema` error #13065

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	if physical_input_schema != physical_input_schema_from_logical {
	return internal_err!("Physical input schema should be the same as the one converted from logical input schema.");
	}

Option to disable Physical input schema should be the same as the one converted from logical schema error #13065

Description

Is your feature request related to a problem or challenge?

Describe the solution you'd like

Describe alternatives you've considered

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alamb commented on Oct 22, 2024

wiedld commented on Oct 22, 2024

alamb commented on Oct 22, 2024

comphead commented on Oct 22, 2024

comphead commented on Oct 22, 2024

findepi commented on Oct 23, 2024

timsaucer commented on Oct 23, 2024

alamb commented on Oct 23, 2024

alamb commented on Oct 23, 2024

comphead commented on Oct 23, 2024

wiedld commented on Oct 23, 2024

findepi commented on Oct 25, 2024

alamb commented on Oct 25, 2024

findepi commented on Oct 25, 2024

alamb commented on Oct 29, 2024

alamb commented on Oct 29, 2024

comphead commented on Oct 29, 2024

alamb commented on Oct 29, 2024

comphead commented on Oct 29, 2024

alamb commented on Oct 29, 2024

comphead commented on Oct 29, 2024

alamb commented on Oct 29, 2024

wiedld commented on Nov 8, 2024

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Option to disable `Physical input schema should be the same as the one converted from logical schema` error #13065