polars_plan/plans/optimizer/predicate_pushdown/mod.rs
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mod group_by;
mod join;
mod keys;
mod rename;
mod utils;
use polars_core::datatypes::PlHashMap;
use polars_core::prelude::*;
use recursive::recursive;
use utils::*;
use super::*;
use crate::dsl::function_expr::FunctionExpr;
use crate::prelude::optimizer::predicate_pushdown::group_by::process_group_by;
use crate::prelude::optimizer::predicate_pushdown::join::process_join;
use crate::prelude::optimizer::predicate_pushdown::rename::process_rename;
use crate::utils::{check_input_node, has_aexpr};
pub type ExprEval<'a> =
Option<&'a dyn Fn(&ExprIR, &Arena<AExpr>, &SchemaRef) -> Option<Arc<dyn PhysicalIoExpr>>>;
pub struct PredicatePushDown<'a> {
expr_eval: ExprEval<'a>,
verbose: bool,
block_at_cache: bool,
}
impl<'a> PredicatePushDown<'a> {
pub fn new(expr_eval: ExprEval<'a>) -> Self {
Self {
expr_eval,
verbose: verbose(),
block_at_cache: true,
}
}
pub(crate) fn block_at_cache(mut self, toggle: bool) -> Self {
self.block_at_cache = toggle;
self
}
fn optional_apply_predicate(
&self,
lp: IR,
local_predicates: Vec<ExprIR>,
lp_arena: &mut Arena<IR>,
expr_arena: &mut Arena<AExpr>,
) -> IR {
if !local_predicates.is_empty() {
let predicate = combine_predicates(local_predicates.into_iter(), expr_arena);
let input = lp_arena.add(lp);
IR::Filter { input, predicate }
} else {
lp
}
}
fn pushdown_and_assign(
&self,
input: Node,
acc_predicates: PlHashMap<PlSmallStr, ExprIR>,
lp_arena: &mut Arena<IR>,
expr_arena: &mut Arena<AExpr>,
) -> PolarsResult<()> {
let alp = lp_arena.take(input);
let lp = self.push_down(alp, acc_predicates, lp_arena, expr_arena)?;
lp_arena.replace(input, lp);
Ok(())
}
/// Filter will be pushed down.
fn pushdown_and_continue(
&self,
lp: IR,
mut acc_predicates: PlHashMap<PlSmallStr, ExprIR>,
lp_arena: &mut Arena<IR>,
expr_arena: &mut Arena<AExpr>,
has_projections: bool,
) -> PolarsResult<IR> {
let inputs = lp.get_inputs_vec();
let exprs = lp.get_exprs();
if has_projections {
// projections should only have a single input.
if inputs.len() > 1 {
// except for ExtContext
assert!(matches!(lp, IR::ExtContext { .. }));
}
let input = inputs[inputs.len() - 1];
let (eligibility, alias_rename_map) =
pushdown_eligibility(&exprs, &[], &acc_predicates, expr_arena)?;
let local_predicates = match eligibility {
PushdownEligibility::Full => vec![],
PushdownEligibility::Partial { to_local } => {
let mut out = Vec::with_capacity(to_local.len());
for key in to_local {
out.push(acc_predicates.remove(&key).unwrap());
}
out
},
PushdownEligibility::NoPushdown => {
return self.no_pushdown_restart_opt(lp, acc_predicates, lp_arena, expr_arena)
},
};
if !alias_rename_map.is_empty() {
for (_, e) in acc_predicates.iter_mut() {
let mut needs_rename = false;
for (_, ae) in (&*expr_arena).iter(e.node()) {
if let AExpr::Column(name) = ae {
needs_rename |= alias_rename_map.contains_key(name);
if needs_rename {
break;
}
}
}
if needs_rename {
// TODO! Do this directly on AExpr.
let mut new_expr = node_to_expr(e.node(), expr_arena);
new_expr = new_expr.map_expr(|e| match e {
Expr::Column(name) => {
if let Some(rename_to) = alias_rename_map.get(&*name) {
Expr::Column(rename_to.clone())
} else {
Expr::Column(name)
}
},
e => e,
});
let predicate = to_aexpr(new_expr, expr_arena)?;
e.set_node(predicate);
}
}
}
let alp = lp_arena.take(input);
let alp = self.push_down(alp, acc_predicates, lp_arena, expr_arena)?;
lp_arena.replace(input, alp);
let lp = lp.with_exprs_and_input(exprs, inputs);
Ok(self.optional_apply_predicate(lp, local_predicates, lp_arena, expr_arena))
} else {
let mut local_predicates = Vec::with_capacity(acc_predicates.len());
// determine new inputs by pushing down predicates
let new_inputs = inputs
.iter()
.map(|&node| {
// first we check if we are able to push down the predicate passed this node
// it could be that this node just added the column where we base the predicate on
let input_schema = lp_arena.get(node).schema(lp_arena);
let mut pushdown_predicates =
optimizer::init_hashmap(Some(acc_predicates.len()));
for (_, predicate) in acc_predicates.iter() {
// we can pushdown the predicate
if check_input_node(predicate.node(), &input_schema, expr_arena) {
insert_and_combine_predicate(
&mut pushdown_predicates,
predicate,
expr_arena,
)
}
// we cannot pushdown the predicate we do it here
else {
local_predicates.push(predicate.clone());
}
}
let alp = lp_arena.take(node);
let alp = self.push_down(alp, pushdown_predicates, lp_arena, expr_arena)?;
lp_arena.replace(node, alp);
Ok(node)
})
.collect::<PolarsResult<Vec<_>>>()?;
let lp = lp.with_exprs_and_input(exprs, new_inputs);
Ok(self.optional_apply_predicate(lp, local_predicates, lp_arena, expr_arena))
}
}
/// Filter will be done at this node, but we continue optimization
fn no_pushdown_restart_opt(
&self,
lp: IR,
acc_predicates: PlHashMap<PlSmallStr, ExprIR>,
lp_arena: &mut Arena<IR>,
expr_arena: &mut Arena<AExpr>,
) -> PolarsResult<IR> {
let inputs = lp.get_inputs();
let exprs = lp.get_exprs();
let new_inputs = inputs
.iter()
.map(|&node| {
let alp = lp_arena.take(node);
let alp = self.push_down(
alp,
init_hashmap(Some(acc_predicates.len())),
lp_arena,
expr_arena,
)?;
lp_arena.replace(node, alp);
Ok(node)
})
.collect::<PolarsResult<Vec<_>>>()?;
let lp = lp.with_exprs_and_input(exprs, new_inputs);
// all predicates are done locally
let local_predicates = acc_predicates.into_values().collect::<Vec<_>>();
Ok(self.optional_apply_predicate(lp, local_predicates, lp_arena, expr_arena))
}
fn no_pushdown(
&self,
lp: IR,
acc_predicates: PlHashMap<PlSmallStr, ExprIR>,
lp_arena: &mut Arena<IR>,
expr_arena: &mut Arena<AExpr>,
) -> PolarsResult<IR> {
// all predicates are done locally
let local_predicates = acc_predicates.into_values().collect::<Vec<_>>();
Ok(self.optional_apply_predicate(lp, local_predicates, lp_arena, expr_arena))
}
/// Predicate pushdown optimizer
///
/// # Arguments
///
/// * `IR` - Arena based logical plan tree representing the query.
/// * `acc_predicates` - The predicates we accumulate during tree traversal.
/// The hashmap maps from leaf-column name to predicates on that column.
/// If the key is already taken we combine the predicate with a bitand operation.
/// The `Node`s are indexes in the `expr_arena`
/// * `lp_arena` - The local memory arena for the logical plan.
/// * `expr_arena` - The local memory arena for the expressions.
#[recursive]
fn push_down(
&self,
lp: IR,
mut acc_predicates: PlHashMap<PlSmallStr, ExprIR>,
lp_arena: &mut Arena<IR>,
expr_arena: &mut Arena<AExpr>,
) -> PolarsResult<IR> {
use IR::*;
match lp {
Filter {
ref predicate,
input,
} => {
// Use a tmp_key to avoid inadvertently combining predicates that otherwise would have
// been partially pushed:
//
// (1) .filter(pl.count().over("key") == 1)
// (2) .filter(pl.col("key") == 1)
//
// (2) can be pushed past (1) but they both have the same predicate
// key name in the hashtable.
let tmp_key = temporary_unique_key(&acc_predicates);
acc_predicates.insert(tmp_key.clone(), predicate.clone());
let local_predicates = match pushdown_eligibility(
&[],
&[(tmp_key.clone(), predicate.clone())],
&acc_predicates,
expr_arena,
)?
.0
{
PushdownEligibility::Full => vec![],
PushdownEligibility::Partial { to_local } => {
let mut out = Vec::with_capacity(to_local.len());
for key in to_local {
out.push(acc_predicates.remove(&key).unwrap());
}
out
},
PushdownEligibility::NoPushdown => {
let out = acc_predicates.drain().map(|t| t.1).collect();
acc_predicates.clear();
out
},
};
if let Some(predicate) = acc_predicates.remove(&tmp_key) {
insert_and_combine_predicate(&mut acc_predicates, &predicate, expr_arena);
}
let alp = lp_arena.take(input);
let new_input = self.push_down(alp, acc_predicates, lp_arena, expr_arena)?;
// TODO!
// If a predicates result would be influenced by earlier applied
// predicates, we simply don't pushdown this one passed this node
// However, we can do better and let it pass but store the order of the predicates
// so that we can apply them in correct order at the deepest level
Ok(
self.optional_apply_predicate(
new_input,
local_predicates,
lp_arena,
expr_arena,
),
)
},
DataFrameScan {
df,
schema,
output_schema,
filter: selection,
} => {
let selection = predicate_at_scan(acc_predicates, selection, expr_arena);
let lp = DataFrameScan {
df,
schema,
output_schema,
filter: selection,
};
Ok(lp)
},
Scan {
mut sources,
file_info,
hive_parts: mut scan_hive_parts,
ref predicate,
mut scan_type,
file_options: options,
output_schema,
} => {
let mut blocked_names = Vec::with_capacity(2);
if let Some(col) = options.include_file_paths.as_deref() {
blocked_names.push(col);
}
match &scan_type {
#[cfg(feature = "parquet")]
FileScan::Parquet { .. } => {},
#[cfg(feature = "ipc")]
FileScan::Ipc { .. } => {},
_ => {
// Disallow row index pushdown of other scans as they may
// not update the row index properly before applying the
// predicate (e.g. FileScan::Csv doesn't).
if let Some(ref row_index) = options.row_index {
blocked_names.push(row_index.name.as_ref());
};
},
};
let local_predicates = if blocked_names.is_empty() {
vec![]
} else {
transfer_to_local_by_name(expr_arena, &mut acc_predicates, |name| {
blocked_names.contains(&name.as_ref())
})
};
let predicate = predicate_at_scan(acc_predicates, predicate.clone(), expr_arena);
if let (Some(hive_parts), Some(predicate)) = (&scan_hive_parts, &predicate) {
if let Some(io_expr) =
self.expr_eval.unwrap()(predicate, expr_arena, &file_info.schema)
{
if let Some(stats_evaluator) = io_expr.as_stats_evaluator() {
let paths = sources.as_paths().ok_or_else(|| {
polars_err!(nyi = "Hive partitioning of in-memory buffers")
})?;
let mut new_paths = Vec::with_capacity(paths.len());
let mut new_hive_parts = Vec::with_capacity(paths.len());
for i in 0..paths.len() {
let path = &paths[i];
let hive_parts = &hive_parts[i];
if stats_evaluator.should_read(hive_parts.get_statistics())? {
new_paths.push(path.clone());
new_hive_parts.push(hive_parts.clone());
}
}
if paths.len() != new_paths.len() {
if self.verbose {
eprintln!(
"hive partitioning: skipped {} files, first file : {}",
paths.len() - new_paths.len(),
paths[0].display()
)
}
scan_type.remove_metadata();
}
if new_paths.is_empty() {
let schema = output_schema.as_ref().unwrap_or(&file_info.schema);
let df = DataFrame::empty_with_schema(schema);
return Ok(DataFrameScan {
df: Arc::new(df),
schema: schema.clone(),
output_schema: None,
filter: None,
});
} else {
sources = ScanSources::Paths(new_paths.into());
scan_hive_parts = Some(Arc::from(new_hive_parts));
}
}
}
}
let mut do_optimization = match &scan_type {
#[cfg(feature = "csv")]
FileScan::Csv { .. } => options.slice.is_none(),
FileScan::Anonymous { function, .. } => function.allows_predicate_pushdown(),
#[cfg(feature = "json")]
FileScan::NDJson { .. } => true,
#[allow(unreachable_patterns)]
_ => true,
};
do_optimization &= predicate.is_some();
let hive_parts = scan_hive_parts;
let lp = if do_optimization {
Scan {
sources,
file_info,
hive_parts,
predicate,
file_options: options,
output_schema,
scan_type,
}
} else {
let lp = Scan {
sources,
file_info,
hive_parts,
predicate: None,
file_options: options,
output_schema,
scan_type,
};
if let Some(predicate) = predicate {
let input = lp_arena.add(lp);
Filter { input, predicate }
} else {
lp
}
};
Ok(self.optional_apply_predicate(lp, local_predicates, lp_arena, expr_arena))
},
Distinct { input, options } => {
if let Some(ref subset) = options.subset {
// Predicates on the subset can pass.
let subset = subset.clone();
let mut names_set = PlHashSet::<PlSmallStr>::with_capacity(subset.len());
for name in subset.iter() {
names_set.insert(name.clone());
}
let condition = |name: &PlSmallStr| !names_set.contains(name.as_str());
let local_predicates =
transfer_to_local_by_name(expr_arena, &mut acc_predicates, condition);
self.pushdown_and_assign(input, acc_predicates, lp_arena, expr_arena)?;
let lp = Distinct { input, options };
Ok(self.optional_apply_predicate(lp, local_predicates, lp_arena, expr_arena))
} else {
let lp = Distinct { input, options };
self.no_pushdown_restart_opt(lp, acc_predicates, lp_arena, expr_arena)
}
},
Join {
input_left,
input_right,
left_on,
right_on,
schema,
options,
} => process_join(
self,
lp_arena,
expr_arena,
input_left,
input_right,
left_on,
right_on,
schema,
options,
acc_predicates,
),
MapFunction { ref function, .. } => {
if function.allow_predicate_pd() {
match function {
FunctionIR::Rename { existing, new, .. } => {
let local_predicates =
process_rename(&mut acc_predicates, expr_arena, existing, new)?;
let lp = self.pushdown_and_continue(
lp,
acc_predicates,
lp_arena,
expr_arena,
false,
)?;
Ok(self.optional_apply_predicate(
lp,
local_predicates,
lp_arena,
expr_arena,
))
},
FunctionIR::Explode { columns, .. } => {
let condition = |name: &PlSmallStr| columns.iter().any(|s| s == name);
// first columns that refer to the exploded columns should be done here
let local_predicates = transfer_to_local_by_name(
expr_arena,
&mut acc_predicates,
condition,
);
let lp = self.pushdown_and_continue(
lp,
acc_predicates,
lp_arena,
expr_arena,
false,
)?;
Ok(self.optional_apply_predicate(
lp,
local_predicates,
lp_arena,
expr_arena,
))
},
#[cfg(feature = "pivot")]
FunctionIR::Unpivot { args, .. } => {
let variable_name = &args
.variable_name
.clone()
.unwrap_or_else(|| PlSmallStr::from_static("variable"));
let value_name = &args
.value_name
.clone()
.unwrap_or_else(|| PlSmallStr::from_static("value"));
// predicates that will be done at this level
let condition = |name: &PlSmallStr| {
name == variable_name
|| name == value_name
|| args.on.iter().any(|s| s == name)
};
let local_predicates = transfer_to_local_by_name(
expr_arena,
&mut acc_predicates,
condition,
);
let lp = self.pushdown_and_continue(
lp,
acc_predicates,
lp_arena,
expr_arena,
false,
)?;
Ok(self.optional_apply_predicate(
lp,
local_predicates,
lp_arena,
expr_arena,
))
},
_ => self.pushdown_and_continue(
lp,
acc_predicates,
lp_arena,
expr_arena,
false,
),
}
} else {
self.no_pushdown_restart_opt(lp, acc_predicates, lp_arena, expr_arena)
}
},
GroupBy {
input,
keys,
aggs,
schema,
apply,
maintain_order,
options,
} => process_group_by(
self,
lp_arena,
expr_arena,
input,
keys,
aggs,
schema,
maintain_order,
apply,
options,
acc_predicates,
),
lp @ Union { .. } => {
let mut local_predicates = vec![];
// a count is influenced by a Union/Vstack
acc_predicates.retain(|_, predicate| {
if has_aexpr(predicate.node(), expr_arena, |ae| matches!(ae, AExpr::Len)) {
local_predicates.push(predicate.clone());
false
} else {
true
}
});
let lp =
self.pushdown_and_continue(lp, acc_predicates, lp_arena, expr_arena, false)?;
Ok(self.optional_apply_predicate(lp, local_predicates, lp_arena, expr_arena))
},
lp @ Sort { .. } => {
let mut local_predicates = vec![];
acc_predicates.retain(|_, predicate| {
if predicate_is_sort_boundary(predicate.node(), expr_arena) {
local_predicates.push(predicate.clone());
false
} else {
true
}
});
let lp =
self.pushdown_and_continue(lp, acc_predicates, lp_arena, expr_arena, false)?;
Ok(self.optional_apply_predicate(lp, local_predicates, lp_arena, expr_arena))
},
// Pushed down passed these nodes
lp @ Sink { .. } => {
self.pushdown_and_continue(lp, acc_predicates, lp_arena, expr_arena, false)
},
lp @ HStack { .. }
| lp @ Select { .. }
| lp @ Reduce { .. }
| lp @ SimpleProjection { .. }
| lp @ ExtContext { .. } => {
self.pushdown_and_continue(lp, acc_predicates, lp_arena, expr_arena, true)
},
// NOT Pushed down passed these nodes
// predicates influence slice sizes
lp @ Slice { .. } => {
self.no_pushdown_restart_opt(lp, acc_predicates, lp_arena, expr_arena)
},
lp @ HConcat { .. } => {
self.no_pushdown_restart_opt(lp, acc_predicates, lp_arena, expr_arena)
},
// Caches will run predicate push-down in the `cache_states` run.
Cache { .. } => {
if self.block_at_cache {
self.no_pushdown(lp, acc_predicates, lp_arena, expr_arena)
} else {
self.pushdown_and_continue(lp, acc_predicates, lp_arena, expr_arena, false)
}
},
#[cfg(feature = "python")]
PythonScan { mut options } => {
let predicate = predicate_at_scan(acc_predicates, None, expr_arena);
if let Some(predicate) = predicate {
// For IO plugins we only accept streamable expressions as
// we want to apply the predicates to the batches.
if !is_streamable(predicate.node(), expr_arena, Default::default())
&& matches!(options.python_source, PythonScanSource::IOPlugin)
{
let lp = PythonScan { options };
return Ok(self.optional_apply_predicate(
lp,
vec![predicate],
lp_arena,
expr_arena,
));
}
options.predicate = PythonPredicate::Polars(predicate);
}
Ok(PythonScan { options })
},
Invalid => unreachable!(),
}
}
pub(crate) fn optimize(
&self,
logical_plan: IR,
lp_arena: &mut Arena<IR>,
expr_arena: &mut Arena<AExpr>,
) -> PolarsResult<IR> {
let acc_predicates = PlHashMap::new();
self.push_down(logical_plan, acc_predicates, lp_arena, expr_arena)
}
}