dosubot[bot] commented on issue #3057:
URL: https://github.com/apache/hugegraph/issues/3057#issuecomment-4657126889

   <!-- Answer -->
   You're right that the task result mechanism isn't suitable for your use 
case. While `task.result_size_limit` is technically a `Long` type, it has a 
**hard upper limit of 1 GB** enforced by a range validator 
[[1]](https://github.com/apache/hugegraph/blob/9126c80e414c073b60fc074361b211cfb409e0eb/hugegraph-server/hugegraph-core/src/main/java/org/apache/hugegraph/config/CoreOptions.java#L292-L298)
 — so even adjusting it won't get you to 2GB+. Additionally, task results are 
stored and retrieved as a single complete compressed blob with no support for 
chunked/paged retrieval 
[[2]](https://github.com/apache/hugegraph/blob/9126c80e414c073b60fc074361b211cfb409e0eb/hugegraph-server/hugegraph-core/src/main/java/org/apache/hugegraph/task/HugeTaskResult.java#L72-L89).
   
   For exporting data exceeding 2GB, the async task result approach 
fundamentally doesn't fit. Instead, consider these alternatives:
   
   **1. `hugegraph-tools` dump/backup commands** (recommended for bulk export):
   
   - Designed specifically for large datasets with shard-based parallel 
processing 
[[3]](https://github.com/apache/hugegraph-toolchain/blob/bc49e6683fcc8f00e32d290cd558a0320c1850a3/hugegraph-tools/src/main/java/org/apache/hugegraph/manager/BackupManager.java#L163-L175)
   - Supports configurable `--split-size`, `--thread-num`, and output to local 
or HDFS 
[[4]](https://github.com/apache/hugegraph-toolchain/blob/bc49e6683fcc8f00e32d290cd558a0320c1850a3/hugegraph-tools/src/main/java/org/apache/hugegraph/cmd/SubCommands.java#L245-L267)
   - Example: `hugegraph-tools dump --split-size 1048576 --thread-num 4 
--directory ./export/`
   
   **2. Scan API with pagination** (for programmatic/custom export):
   
   - Use `/graphs/{graph}/graph/vertices/scan` with `start`, `end`, and `page` 
parameters 
[[5]](https://github.com/apache/hugegraph/blob/9126c80e414c073b60fc074361b211cfb409e0eb/hugegraph-server/hugegraph-api/src/main/java/org/apache/hugegraph/api/traversers/VerticesAPI.java#L103-L130)
   - Split the keyspace into shards via 
`/graphs/{graph}/graph/vertices/shards?split_size=...`
   - Iterate through shards to export incrementally without hitting memory 
limits
   
   **3. Gremlin pagination** (for filtered queries):
   
   - Use `.range(start, end)` in your Gremlin query to paginate results 
client-side
   
   These approaches let you stream/paginate results rather than materializing 
everything into a single task result, which is the core problem with the 
current approach.
   
   
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