rdsr commented on a change in pull request #1748:
URL: https://github.com/apache/iceberg/pull/1748#discussion_r522302920
##########
File path: site/docs/hive.md
##########
@@ -50,6 +50,38 @@ You should now be able to issue Hive SQL `SELECT` queries
using the above table
SELECT * from table_a;
```
+#### Using Hive Catalog
+Iceberg tables created using `HiveCatalog` are automatically registered with
Hive.
+
+##### Create an Iceberg table
+The first step is to create an Iceberg table using the Spark/Java/Python API
and `HiveCatalog`. For the purposes of this documentation we will assume that
the table is called `table_b` and that the table location is
`s3://some_path/table_b`. In order for Iceberg to correctly set up the Hive
table for querying some configuration values need to be set, the two options
for this are described below - you can use either or the other depending on
your use case.
+
+##### Hive Configuration
+The value `iceberg.engine.hive.enabled` needs to be set to `true` and added to
the Hive configuration file on the classpath of the application creating the
table. This can be done by modifying the relevant `hive-site.xml`.
Alternatively this can done programatically like so:
Review comment:
I assume we can query existing Iceberg tables also through Hive by
setting the `iceberg.engine.hive.enabled` flag? Do you think it worth calling
that out?
##########
File path: site/docs/hive.md
##########
@@ -50,6 +50,38 @@ You should now be able to issue Hive SQL `SELECT` queries
using the above table
SELECT * from table_a;
```
+#### Using Hive Catalog
+Iceberg tables created using `HiveCatalog` are automatically registered with
Hive.
+
+##### Create an Iceberg table
+The first step is to create an Iceberg table using the Spark/Java/Python API
and `HiveCatalog`. For the purposes of this documentation we will assume that
the table is called `table_b` and that the table location is
`s3://some_path/table_b`. In order for Iceberg to correctly set up the Hive
table for querying some configuration values need to be set, the two options
for this are described below - you can use either or the other depending on
your use case.
+
+##### Hive Configuration
+The value `iceberg.engine.hive.enabled` needs to be set to `true` and added to
the Hive configuration file on the classpath of the application creating the
table. This can be done by modifying the relevant `hive-site.xml`.
Alternatively this can done programatically like so:
+```java
+Configuration hadoopConfiguration = spark.sparkContext().hadoopConfiguration();
+hadoopConfiguration.set(ConfigProperties.ENGINE_HIVE_ENABLED, "true");
//iceberg.engine.hive.enabled=true
+HiveCatalog catalog = new HiveCatalog(hadoopConfiguration);
+...
+catalog.createTable(tableId, schema, spec);
+```
+
+##### Table Property Configuration
+The property `engine.hive.enabled` needs to be set to `true` and added to the
table properties when creating the Iceberg table. This can be done like so:
+```java
+ Map<String, String> tableProperties = new HashMap<String, String>();
+ tableProperties.put(TableProperties.ENGINE_HIVE_ENABLED, "true");
////engine.hive.enabled=true
+ catalog.createTable(tableId, schema, spec, tableProperties);
+```
+
+#### Query the Iceberg table via Hive
+TODO: tables created by the above can't just be read "as is", need to document
steps needed in order to be able to query them here.
Review comment:
This seems to me contradictory to the following lines. Is this TODO
still valid?
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