ClickHouse DB::Exception: Too many retries to fetch parts

The DB::Exception: Too many retries to fetch parts error (code TOO_MANY_RETRIES_TO_FETCH_PARTS) signals that a replica has exhausted its retry budget while trying to download a data part from another replica. After multiple unsuccessful attempts, ClickHouse gives up on the fetch and marks it as failed in the replication queue.

Impact

The replica falls behind because it cannot obtain the required data parts. Queries directed to this node may return stale or incomplete results. If merges depend on the missing part, they will also be blocked, potentially leading to a growing backlog in the replication queue. Over time this can snowball into significant replication lag.

Common Causes

1. Network instability between replicas -- packet loss, high latency, or intermittent connectivity causes repeated transfer failures.
2. Source replica is overloaded -- the replica holding the part cannot serve it because of CPU, disk I/O, or memory pressure.
3. Part was merged or removed on the source before the fetch could complete, making it unavailable.
4. Interserver HTTP port misconfiguration -- the interserver_http_port (default 9009) is blocked by a firewall or bound to the wrong interface.
5. Disk space exhaustion on the fetching replica, causing the download to fail mid-transfer.
6. Large part size combined with a short timeout -- very large parts take longer to transfer than the configured timeout allows.

Troubleshooting and Resolution Steps

1. Examine the replication queue for details

   SELECT database, table, type, new_part_name, num_tries, last_exception, last_attempt_time
   FROM system.replication_queue
   WHERE last_exception LIKE '%fetch%' OR num_tries > 5
   ORDER BY num_tries DESC;
   

2. Test inter-replica connectivity From the failing node, verify the interserver port is reachable:

   curl -v http://source-replica:9009/
   

   Check firewall rules, security groups, and DNS resolution.

3. Check source replica health On the replica that should be serving the part:

   SELECT name, active, bytes_on_disk
   FROM system.parts
   WHERE table = 'my_table' AND name = 'the_part_name';
   

   Also review CPU and disk I/O metrics to confirm it is not under excessive load.

4. Verify disk space on the fetching node

   df -h /var/lib/clickhouse
   

   Ensure there is enough space for the part being fetched plus a safety margin.

5. Increase fetch-related timeouts If parts are large, increase the relevant settings:

   <replicated_fetches_http_connection_timeout>60</replicated_fetches_http_connection_timeout>
   <replicated_fetches_http_receive_timeout>300</replicated_fetches_http_receive_timeout>
   

6. Restart replication on the affected table

   SYSTEM RESTART REPLICA db.my_table;
   

   This resets the retry counters and re-evaluates the queue.

7. Manually trigger a fetch from a specific replica If the part exists on another replica that is healthy:

   SYSTEM SYNC REPLICA db.my_table;
   

Best Practices

• Monitor system.replication_queue for entries with high num_tries counts as an early warning sign.
• Ensure all replicas can reach each other on the interserver HTTP port without traversing unreliable network paths.
• Size network bandwidth and disk I/O capacity to handle the expected replication throughput.
• Keep replicas on similar hardware specs to avoid one slow node becoming a bottleneck.
• Use replicated_max_parallel_fetches to limit concurrent fetches if network contention is an issue.

Frequently Asked Questions

Q: Will the fetch retry automatically after the error?
A: ClickHouse keeps the entry in the replication queue and will retry periodically. However, once the retry limit is hit, the backoff interval increases significantly. Running SYSTEM RESTART REPLICA resets the counters.

Q: Can I increase the maximum number of retries?
A: The retry behavior is mostly governed by internal logic and backoff timers rather than a single configurable limit. Increasing timeouts and fixing the root cause is more effective.

Q: Does this error cause data loss?
A: No. The data still exists on other replicas. Once the fetch succeeds, the local replica will have the part and be consistent again.

Q: What if the part no longer exists on any replica?
A: Then you will encounter the NO_REPLICA_HAS_PART error instead. In that case, consider restoring from a backup or re-ingesting the data.