gfphoenix78 commented on code in PR #1333:
URL: https://github.com/apache/cloudberry/pull/1333#discussion_r2496681379
##########
contrib/pax_storage/src/cpp/storage/micro_partition_row_filter_reader.cc:
##########
@@ -73,6 +75,109 @@ MicroPartitionRowFilterReader::GetNextGroup(TupleDesc desc)
{
return group_;
}
+void MicroPartitionRowFilterReader::LoadExprFilterColumns(
+ MicroPartitionReader::Group *group, TupleDesc desc,
+ const ExecutionFilterContext *ctx, size_t row_index, TupleTableSlot *slot)
{
+ // There will not be duplicate attnos here because the attnos in ctx come
from
+ // qual expressions. For each column index, there is at most one
corresponding
+ // attno in ctx->attnos, so no attno appears more than once. As a result,
this
+ // loop does not load the same column multiple times.
+ for (int i = 0; i < ctx->size; i++) {
+ auto attno = ctx->attnos[i];
+ Assert(attno > 0);
+ std::tie(slot->tts_values[attno - 1], slot->tts_isnull[attno - 1]) =
+ group->GetColumnValue(desc, attno - 1, row_index);
+ }
+}
+
+bool MicroPartitionRowFilterReader::EvalBloomNode(
+ const ExecutionFilterContext *ctx, MicroPartitionReader::Group *group,
+ TupleDesc desc, size_t row_index, int bloom_index) {
+ Assert(bloom_index >= 0 &&
+ (size_t)bloom_index < ctx->runtime_bloom_keys.size());
+ const auto &skd = ctx->runtime_bloom_keys[bloom_index];
+ const ScanKey sk = const_cast<ScanKeyData *>(&skd);
+ bool isnull = false;
+ Datum val;
+ std::tie(val, isnull) =
+ group->GetColumnValue(desc, sk->sk_attno - 1, row_index);
+ if (isnull) return true;
+ bloom_filter *bf = (bloom_filter *)DatumGetPointer(sk->sk_argument);
+ return !bloom_lacks_element(bf, (unsigned char *)&val, sizeof(Datum));
+}
+
+bool MicroPartitionRowFilterReader::EvalExprNode(
+ const ExecutionFilterContext *ctx, TupleTableSlot *slot, int expr_index) {
+ return TestRowScanInternal(slot, ctx->estates[expr_index],
+ ctx->attnos[expr_index]);
+}
+
+// Execute a filter node.
+// During the sampling phase, updates the filter's pass rate statistics.
+bool MicroPartitionRowFilterReader::EvalFilterNode(
+ ExecutionFilterContext *ctx, MicroPartitionReader::Group *group,
+ TupleDesc desc, size_t row_index, TupleTableSlot *slot,
+ ExecutionFilterContext::FilterNode &node, bool update_stats) {
+ bool pass = true;
+ if (node.kind == ExecutionFilterContext::FilterKind::kBloom) {
+ pass = EvalBloomNode(ctx, group, desc, row_index, node.index);
+ if (ctx->ps->instrument && !pass) ctx->ps->instrument->nfilteredPRF += 1;
+ } else {
+ pass = EvalExprNode(ctx, slot, node.index);
+ }
+ if (update_stats) {
+ node.tested++;
+ node.passed += pass ? 1 : 0;
+ }
+ return pass;
+}
+
+// Applies the row filter nodes to the current tuple in two phases: Sampling
and
+// Filtering.
+// In the sampling phase, pass rates for each filter expression are collected
on
+// the first 64k rows, then the filters are sorted by effectiveness (lower pass
+// rate first) for optimal filtering order.
+// In the filtering phase, filters are applied in the determined order with
+// short-circuit evaluation; a failure in any filter causes immediate rejection
+// of the tuple.
+bool MicroPartitionRowFilterReader::ApplyFiltersWithSampling(
+ ExecutionFilterContext *ctx, MicroPartitionReader::Group *group,
+ TupleDesc desc, size_t row_index, TupleTableSlot *slot) {
+ if (!ctx->sampling) {
+ for (auto &node : ctx->filter_nodes) {
+ if (!EvalFilterNode(ctx, group, desc, row_index, slot, node, false)) {
+ return false;
+ }
+ }
+ return true;
+ }
+
+ ctx->sample_rows++;
+ bool all_pass = true;
+ // in the sampling phase, we need to evaluate all filter nodes, if any node
+ // fails, the tuple is rejected
+ for (auto &node : ctx->filter_nodes) {
+ if (!EvalFilterNode(ctx, group, desc, row_index, slot, node, true)) {
+ all_pass = false;
Review Comment:
Is it meaningful to evaluate the next filter if all_pass is false?
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