get_compaction_plans()

This operation returns the compaction plans for a specific compaction job, including the merge plans showing which segments will be combined.

Request syntax

client.get_compaction_plans(
    job_id: int,
    timeout: float = None
) -> CompactionPlans

PARAMETERS:

• job_id (int) -

  [REQUIRED]

  The ID of the compaction job returned by compact().

• timeout (float | None) -

  The timeout duration for this operation. Setting this to None indicates that this operation timeouts when any response arrives or any error occurs.

RETURN TYPE:

CompactionPlans

RETURNS:

A CompactionPlans object with the following members:

• compaction_id (int) -

  The ID of the compaction job.

• collection_name (str) -

  The name of the collection that the compaction job runs on. Available in PyMilvus v3.0.2 or later. When retrieved through get_compaction_plans(), this member is empty; use list_compaction_tasks() to obtain it.

• state (State) -

  The overall state of the compaction job. Possible values are UndefiedState, Executing, and Completed.

• plans (List[Plan]) -

  The merge plans of the compaction job. Each Plan object has the following members:

  • plan_id (int) -

    The ID of this compaction plan.

  • task_id (int) -

    An alias of plan_id.

  • trigger_id (int) -

    The ID of the compaction trigger.

  • collection_id (int) -

    The ID of the collection being compacted.

  • partition_id (int) -

    The ID of the partition being compacted.

  • channel (str) -

    The insert channel that the segments belong to.

  • compaction_type (CompactionType) -

    The type of this compaction.

  • state (CompactionTaskState) -

    The state of this compaction plan.

  • failure_reason (str) -

    The reason why this plan failed, or an empty string.

  • sources (list) -

    The IDs of the source segments to merge.

  • target (int) -

    The ID of the target segment.

  • targets (List[int]) -

    The IDs of the target segments. Falls back to target when the server does not return multiple targets.

EXCEPTIONS:

• MilvusException

  This exception will be raised when any error occurs during this operation.

Example

from pymilvus import MilvusClient

client = MilvusClient(
    uri="http://localhost:19530",
    token="root:Milvus"
)

# Create a collection and insert some data
client.create_collection(collection_name="my_collection", dimension=5)
client.insert(collection_name="my_collection", data=[{"id": i, "vector": [0.1] * 5} for i in range(10)])

# Flush the data so that the inserted segments are sealed and become compactable
client.flush(collection_name="my_collection")

job_id = client.compact(collection_name="my_collection")
plans = client.get_compaction_plans(job_id=job_id)
print(plans)