[GitHub] [iceberg] kbendick commented on a change in pull request #3745: Push down partition filter to Spark when Importing File Based Tables

[GitBox <gi...@apache.org>]

kbendick commented on a change in pull request #3745:
URL: https://github.com/apache/iceberg/pull/3745#discussion_r769142116



##########
File path: spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/Spark3Util.java
##########
@@ -766,9 +774,22 @@ public static TableIdentifier identifierToTableIdentifier(Identifier identifier)
 
     org.apache.spark.sql.execution.datasources.PartitionSpec spec = fileIndex.partitionSpec();
     StructType schema = spec.partitionColumns();
+    if (schema.isEmpty()) {
+      return new ArrayList<>();
+    }
+
+    List<org.apache.spark.sql.catalyst.expressions.Expression> filterExpressions =
+        getPartitionFilterExpressions(schema, partitionFilter);
+
+    List<org.apache.spark.sql.catalyst.expressions.Expression> dataFilters = new java.util.ArrayList<>();

Review comment:
       Nit: Same note about avoiding `new ArrayList<>` in favor of one of the ones mentioned above 👍 

##########
File path: spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/Spark3Util.java
##########
@@ -779,10 +800,54 @@ public static TableIdentifier identifierToTableIdentifier(Identifier identifier)
             Object value = CatalystTypeConverters.convertToScala(catalystValue, field.dataType());
             values.put(field.name(), value.toString());
           });
-          return new SparkPartition(values, partition.path().toString(), format);
+          FileStatus fileStatus =
+              scala.collection.JavaConverters.seqAsJavaListConverter(partition.files()).asJava().get(0);
+
+          return new SparkPartition(values, fileStatus.getPath().getParent().toString(), format);
         }).collect(Collectors.toList());
   }
 
+  private static List getPartitionFilterExpressions(StructType schema,
+                                                    Map<String, String> partitionFilter) {
+    List<org.apache.spark.sql.catalyst.expressions.Expression> filterExpressions = new java.util.ArrayList<>();
+    for (Map.Entry<String, String> entry : partitionFilter.entrySet()) {
+      try {
+        // IllegalArgumentException is thrown if schema doesn't contain this entry,
+        // which means partition filter is not on partition columns.
+        int index = schema.fieldIndex(entry.getKey());
+        org.apache.spark.sql.types.DataType dataType = schema.fields()[index].dataType();
+        BoundReference ref = new BoundReference(index, dataType, true);
+        if (dataType.sameType(DataTypes.IntegerType) || dataType.sameType(DataTypes.ShortType) ||
+            dataType.sameType(DataTypes.ByteType)) {
+          filterExpressions.add(new EqualTo(ref,
+              org.apache.spark.sql.catalyst.expressions.Literal.create(Integer.parseInt(entry.getValue()),
+              DataTypes.IntegerType)));
+        } else if (schema.fields()[index].dataType().sameType(DataTypes.StringType)) {
+          filterExpressions.add(new EqualTo(ref,
+              org.apache.spark.sql.catalyst.expressions.Literal.create(entry.getValue(), DataTypes.StringType)));
+        } else if (schema.fields()[index].dataType().sameType(DataTypes.LongType)) {
+          filterExpressions.add(new EqualTo(ref,
+              org.apache.spark.sql.catalyst.expressions.Literal.create(Long.parseLong(entry.getValue()),
+              DataTypes.LongType)));
+        } else if (schema.fields()[index].dataType().sameType(DataTypes.DateType)) {
+          filterExpressions.add(new EqualTo(ref,
+              org.apache.spark.sql.catalyst.expressions.Literal.create(entry.getValue(), DataTypes.DateType)));
+        } else if (schema.fields()[index].dataType().sameType(DataTypes.TimestampType)) {
+          filterExpressions.add(new EqualTo(ref,
+              org.apache.spark.sql.catalyst.expressions.Literal.create(entry.getValue(), DataTypes.TimestampType)));
+        } else if (schema.fields()[index].dataType()
+            .sameType(DataTypes.CalendarIntervalType)) {
+          filterExpressions.add(new EqualTo(ref,
+              org.apache.spark.sql.catalyst.expressions.Literal.create(entry.getValue(),
+              DataTypes.CalendarIntervalType)));

Review comment:
       For this large if-else-if chain, you might want to look into this lookup-map pattern used here: https://github.com/apache/iceberg/blob/466073b7d8c23ebeae045822ee6e1a1104a5ed5a/spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/SparkFilters.java#L80-L220
   
   I'm not sure if a look-up map can be used here because of the usage of `sameType` function, but it might be worth looking into 😄 

##########
File path: spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/Spark3Util.java
##########
@@ -766,9 +774,22 @@ public static TableIdentifier identifierToTableIdentifier(Identifier identifier)
 
     org.apache.spark.sql.execution.datasources.PartitionSpec spec = fileIndex.partitionSpec();
     StructType schema = spec.partitionColumns();
+    if (schema.isEmpty()) {
+      return new ArrayList<>();

Review comment:
       Nit: Can you use `Lists.newArrayList()` or `ImmutableList.empty()` here?
   
   For `Lists`, we use the repackaged internal guava version from `org.apache.iceberg.relocated.com.google.common.collect.Lists`. The same is true for `ImmutableList`, which is already imported.
   
   You could also use `Collections.emptyList()` to be similar to the `emptyMap` above.




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