rdblue commented on a change in pull request #1783:
URL: https://github.com/apache/iceberg/pull/1783#discussion_r539490195
##########
File path:
spark3/src/main/java/org/apache/iceberg/spark/source/IcebergSource.java
##########
@@ -19,22 +19,49 @@
package org.apache.iceberg.spark.source;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
import java.util.Map;
-import org.apache.hadoop.conf.Configuration;
-import org.apache.iceberg.Table;
-import org.apache.iceberg.catalog.TableIdentifier;
-import org.apache.iceberg.hadoop.HadoopTables;
-import org.apache.iceberg.hive.HiveCatalog;
-import org.apache.iceberg.hive.HiveCatalogs;
import org.apache.iceberg.relocated.com.google.common.base.Preconditions;
+import org.apache.iceberg.relocated.com.google.common.collect.ImmutableMap;
+import org.apache.iceberg.spark.PathIdentifier;
+import org.apache.iceberg.spark.Spark3Util;
+import org.apache.iceberg.spark.SparkCatalog;
+import org.apache.iceberg.spark.SparkSessionCatalog;
import org.apache.spark.sql.SparkSession;
-import org.apache.spark.sql.connector.catalog.TableProvider;
+import org.apache.spark.sql.catalyst.analysis.NoSuchTableException;
+import org.apache.spark.sql.catalyst.parser.ParseException;
+import org.apache.spark.sql.connector.catalog.CatalogManager;
+import org.apache.spark.sql.connector.catalog.CatalogPlugin;
+import org.apache.spark.sql.connector.catalog.Identifier;
+import org.apache.spark.sql.connector.catalog.SupportsCatalogOptions;
+import org.apache.spark.sql.connector.catalog.Table;
+import org.apache.spark.sql.connector.catalog.TableCatalog;
import org.apache.spark.sql.connector.expressions.Transform;
import org.apache.spark.sql.sources.DataSourceRegister;
import org.apache.spark.sql.types.StructType;
import org.apache.spark.sql.util.CaseInsensitiveStringMap;
-public class IcebergSource implements DataSourceRegister, TableProvider {
+/**
+ * The IcebergSource loads/writes tables with format "iceberg". It can load
paths and tables.
+ *
+ * How paths/tables are loaded when using
spark.read().format("iceberg").path(table)
+ *
+ * table = "file:/path/to/table" -> loads a HadoopTable at given path
+ * table = "catalog.`file:/path/to/table`" -> loads a HadoopTable at given
path using settings from 'catalog'
+ * table = "catalog.namespace.`file:/path/to/table`" -> fails. Namespace
doesn't exist for paths
+ * table = "tablename" -> loads currentCatalog.currentNamespace.tablename
+ * table = "xxx.tablename" -> if xxx is a catalog load "tablename" from the
specified catalog. Otherwise
+ * load "xxx.tablename" from current catalog
+ * table = "xxx.yyy.tablename" -> if xxx is a catalog load "yyy.tablename"
from the specified catalog. Otherwise
+ * load "xxx.yyy.tablename" from current catalog
Review comment:
In these examples, I think it is easier to understand if you separate
the cases and use `catalog` and `namespace`, rather than "if xxx is a catalog .
. . otherwise . . .".
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