zhoulii commented on code in PR #10950:
URL: https://github.com/apache/paimon/pull/10950#discussion_r4453065561
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paimon-spark/paimon-spark-common/src/main/scala/org/apache/paimon/spark/catalyst/analysis/expressions/ExpressionUtils.scala:
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@@ -18,5 +18,42 @@
package org.apache.paimon.spark.catalyst.analysis.expressions
+import org.apache.paimon.predicate.Predicate
+import org.apache.paimon.types.RowType
+
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.optimizer.{ConstantFolding, SimplifyCasts}
+import org.apache.spark.sql.catalyst.plans.logical.Filter
+import org.apache.spark.sql.catalyst.trees.TreePattern.CURRENT_LIKE
+import org.apache.spark.sql.execution.datasources.v2.DataSourceV2Relation
+
/** This wrapper is only used in java code, e.g. Procedure. */
-object ExpressionUtils extends ExpressionHelper
+object ExpressionUtils extends ExpressionHelper {
+
+ def convertPolicyFilter(
+ spark: SparkSession,
+ relation: DataSourceV2Relation,
+ rowType: RowType,
+ filterSql: String): Predicate = {
+ val parsed = spark.sessionState.sqlParser.parseExpression(filterSql)
+ val analyzed = spark.sessionState.analyzer.execute(Filter(parsed,
relation))
+ spark.sessionState.analyzer.checkAnalysis(analyzed)
+ val filter = analyzed.asInstanceOf[Filter]
+ val condition = filter.condition
+ // Query-context values must not be frozen into a persistent authorization
rule.
+ require(
+ !condition.containsPattern(CURRENT_LIKE),
+ "filter_sql cannot contain expressions that depend on the current query
context."
+ )
+
+ val normalized =
SimplifyCasts(ConstantFolding(filter)).asInstanceOf[Filter].condition
+ // A stored policy has no engine-side residual filter, so every conjunct
must convert.
+ convertConditionToPaimonPredicate(
Review Comment:
Fixed the signed-zero comparisons for FLOAT/DOUBLE. Timestamp precision is
also normalized; legacy timestamp comparisons and nested timestamp comparisons
with precision above 6 are rejected before storing a policy.
Added end-to-end REST authorization tests with expected results evaluated
independently using Spark `VALUES` queries.
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