Metadata Table

A metadata table is a special Hudi metadata table, which is hidden from users. The table stores metadata of a common Hudi table.

The metadata table is included in a common Hudi table and has a one-to-one mapping relationship with the Hudi table.

Listing massive table partition files in HDFS consumes a large number of RPC requests, reducing HDFS throughput and affecting performance. This problem is more serious for object storage such as OBS. However, a query engine must go through the preceding step before a query.

Generally, partition information of the current partitioned table is stored in Hive MetaStore. If the partition size of a partitioned table reaches a certain level, the query engine performance deteriorates significantly when querying the partition information of the current table.

A metadata table stores the partition information of the current Hudi table and the file information in the partition directory as the metadata information in a special Hudi table. In this way, when a query engine lists partition files of the table, the engine only needs access the metadata table. The RPC pressure of HDFS during query can be greatly reduced with a small volume of metadata information.

A metadata table is implemented using a Hudi MOR table. Therefore, it can be compacted, cleaned up, and incrementally updated. Unlike similar implementations in other projects, the file listing information is indexed as HFiles, which offers point-lookup performance to obtain partition file listings.

For Hive query, run set hoodie.metadata.enable=true.

For Spark SQL query, set --conf spark.hadoop.hoodie.metadata.enable to true when starting Spark SQL.

When using Spark to write data, set hoodie.metadata.enable in the option parameter to true.

For details about more parameters, see Configuration Reference or visit Hudi official website http://hudi.apache.org/docs/configurations.html#metadata-config.

In the test on a large table with 250,000 partition files, the metadata table delivers two to three times speedup over parallelized listing done by Spark.

1. Do not manually operate a metadata table. Otherwise, data security may be affected.
2. To use metadata, you must enable metadata for each write operation to ensure data integrity.
3. When compaction and rollback are performed on tables of Hudi 0.8, data cannot be synchronized to the metadata table.
4. When metadata is enabled during the clean operation, the metadata table can be updated.
5. When the number of commits reaches a specified value, compaction, clean, and archive operations are automatically triggered. Therefore, the operation in 1 is unnecessary.