uros-b commented on code in PR #17537:
URL: https://github.com/apache/iceberg/pull/17537#discussion_r3735215755


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site/docs/blog/posts/2026-08-10-variant-in-apache-iceberg.md:
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+---
+date: 2026-08-10
+title: "Semi-Structured Data in Apache Iceberg: Meet the Variant Type"
+slug: variant-in-apache-iceberg
+authors:
+  - nssalian
+categories:
+  - blog
+---
+
+<!--
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+ -
+ -   http://www.apache.org/licenses/LICENSE-2.0
+ -
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+ - distributed under the License is distributed on an "AS IS" BASIS,
+ - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ - limitations under the License.
+ -->
+
+Semi-structured data, such as JSON-like documents whose fields differ from row 
to row, has always been a poor fit for table formats built around fixed 
schemas. Iceberg v3 adds the Variant type for exactly this data: a single 
column can hold values of arbitrary, evolving shape, stored in a compact binary 
form that engines read and write consistently.
+
+This is the first post in a series on Variant in Apache Iceberg. It covers 
what Variant is, why it exists, and how it fits into an Iceberg table. Later 
posts cover shredding, the technique that stores frequently accessed Variant 
fields as typed, columnar data. Variant is stored in Parquet, Avro, and ORC; 
shredding is currently available only in Parquet.
+
+<!-- more -->
+
+## What is Variant?
+
+Variant is a self-describing type for semi-structured data. A single Variant 
column can hold objects, arrays, and primitive values.
+
+## Why Variant?
+
+Consider event data whose shape changes over time:
+
+```json
+{"timestamp": "2026-01-15T10:30:00Z", "user": 5, "event": "login"}
+{"timestamp": "2026-01-15T11:45:00Z", "user": 5, "event": "purchase", 
"amount": 99.99}
+{"timestamp": "2026-01-15T12:00:00Z", "user": 7, "event": "login", "device": 
"mobile"}
+```
+
+Two traditional approaches handle this, and both have drawbacks:
+
+- **JSON stored as a string.** This is flexible, but reading a single field 
means parsing the whole text. JSON's type system is also thin: a timestamp is 
just a string, and a number's precision is ambiguous.
+- **A rigid, flattened schema.** This is fast to query, but every new field is 
a schema migration, and sparse or one-off fields waste space.
+
+Binary encodings such as BSON store values in binary form, but they still 
repeat every field name (`"timestamp"`, `"user"`, `"event"`) in every row.
+
+Variant is as flexible as JSON but stores data in a compact, typed binary 
form. Values keep their native types: a timestamp stays a timestamp and a 
decimal keeps its precision, instead of collapsing to JSON's strings and 
numbers. Field names are stored once in binary, so there is none of the per-row 
string overhead of JSON or BSON. No schema is declared up front, so documents 
of different shapes coexist in one column and a new field needs no migration.
+
+## Variant in Apache Iceberg
+
+Variant was added to the Iceberg type system in the v3 spec, alongside other 
v3 extensions such as nanosecond timestamps and the `geometry` and `geography` 
types. The spec places it in its own category: `variant` is "neither a 
primitive type nor a nested type." It is richer than a primitive, yet has no 
fixed, declared shape the way a struct or list does.
+
+A Variant value is similar to JSON, but with a wider set of primitives 
including `date`, `timestamp`, `timestamptz`, `binary`, and `decimal`. It can 
also nest:
+
+1. A **Variant array** is an ordered collection of Variant values. Unlike an 
Iceberg list, its elements are not constrained to a single element type.
+2. A **Variant object** is a collection of string-keyed fields whose values 
are themselves Variant values. Unlike an Iceberg struct, its fields are not a 
fixed, named set of typed columns.
+
+### How it is stored
+
+Iceberg does not define its own binary encoding for Variant. The type and its 
encoding come from the [Apache Parquet 
project](https://github.com/apache/parquet-format/blob/master/VariantEncoding.md),
 and Iceberg uses that encoding as-is, so a `variant` column maps to a Parquet 
`group` with two binary fields:
+
+```parquet
+optional group event_data (VARIANT(1)) {
+  required binary metadata;
+  required binary value;
+}
+```
+
+- `metadata` holds the dictionary of field names shared across the value, so 
names are stored once instead of per row.
+- `value` holds the data itself in compact binary form: primitives, arrays, 
and objects.
+
+Both fields are accessed by name and carry no Iceberg field IDs. Variant is 
stored as this `metadata` + `value` pair in Parquet, Avro, and ORC. One 
optimization sets Parquet apart: shredding is supported only there. In Avro and 
ORC, a Variant is always the single unshredded pair.
+
+### Reading and writing across engines
+
+- **Apache Spark 4.0 and 4.1** create tables with `VARIANT` columns and read 
and write them. Reading landed in Iceberg 1.10.0 on Spark 4.0; Iceberg 1.11.0 
added Spark 4.1 and writing shredded Variant on both Spark 4.0 and 4.1.
+- **Apache Flink 2.1** added Variant support in Iceberg 1.11.0.

Review Comment:
   +1 with @Guosmilesmile's comment. Shredded-write support for Flink (PR 
#15596) was merged to main after 1.11.0 and is milestoned for 1.12.0, so not 
yet released.



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