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layout: page title: Iceberg Support in Velox Backend nav_order: 8 parent: Getting-Started

Iceberg Support in Velox Backend

Supported Spark version

All the spark version is supported, but for convenience, only Spark 3.4 is well tested. Now only read is supported in Gluten.

Support Status

Following value indicates the iceberg support progress:

Value	Description
Offload	Offload to the Velox backend
PartialOffload	Some operators offload and some fallback
Fallback	Fallback to spark to execute
Exception	Cannot fallback by some conditions, throw the exception
ResultMismatch	Some hidden bug may cause result mismatch, especially for some corner case

Adding catalogs

Fallback

Creating a table

Fallback

Writing

Fallback

INSERT INTO local.db.table VALUES (1, 'a'), (2, 'b'), (3, 'c');

PartialOffload

The write is fallback while read is offload.

INSERT INTO local.db.table SELECT id, data FROM source WHERE length(data) = 1;

Reading

Read data

Offload/Fallback

Table Type	No Delete	Position Delete	Equality Delete
unpartition	Offload	Offload	Fallback
partition	Fallback mostly	Fallback mostly	Fallback
metadata	Fallback

Offload the simple query.

SELECT count(1) as count, data
FROM local.db.table
GROUP BY data;

If delete by Spark and copy on read, will generate position delete file, the query may offload.

If delete by Flink, may generate the equality delete file, fallback in tht case.

Now we only offload the simple query, for partition table, many operators are fallback by Expression StaticInvoke such as BucketFunction, wait to be supported.

DataFrame reads are supported and can now reference tables by name using spark.table:

val df = spark.table("local.db.table")
df.count()

Read metadata

Fallback

SELECT data, _file FROM local.db.table;

DataType

Timestamptz in orc format is not supported, throws exception. UUID type and Fixed type is fallback.

Format

PartialOffload

Supports parquet and orc format. Not support avro format.

SQL

Only support SELECT.

Schema evolution

PartialOffload

Gluten uses column name to match the parquet file, so if the column is renamed or the added column name is same to the deleted column, the scan will fall back.

Configuration

Catalogs

Supports all the catalog options, which is not used in native engine.

SQL Extensions

Fallback

Supports the option spark.sql.extensions, fallback the SQL command CALL.

Runtime configuration

Read options

Spark option	Status
snapshot-id	Support
as-of-timestamp	Support
split-size	Support
lookback	Support
file-open-cost	Support
vectorization-enabled	Not Support
batch-size	Not Support