@Rocky I have a nifi process that calls a stream load, i have a cluster of 6 nifi nodes so the http request normally happens at the same time and one will timeout, should I stagger them?

Staggering the requests is a common manual workaround, but StarRocks provides more efficient ways to handle high concurrency. If your 6 NiFi nodes are hitting the cluster simultaneously and causing timeouts, it is likely due to one of three things: transaction lock contention, BE (Backend) resource limits, or NiFi's internal HTTP timeouts. Recommended Solutions 1. Enable Merge Commit (Recommended for v3.4.0+) If you are on StarRocks v3.4.0 or later, use the Merge Commit feature. This is specifically designed for high-concurrency, small-batch scenarios. It allows StarRocks to automatically merge multiple concurrent Stream Load requests into a single transaction. * Why: It reduces the number of data versions and transaction lock contention in the Frontend (FE). * How: Add the following to your HTTP headers in the NiFi request:

http
    enable_merge_commit: true

* Note: This is ideal if you are loading into the same table. 2. Check and Increase Timeouts If NiFi is the one timing out before StarRocks responds, check both ends: * NiFi Side: Ensure the

Connection Timeout

and

Read Timeout

in your

InvokeHTTP

(or similar processor) are long enough (e.g., 600s to match StarRocks defaults). * StarRocks Side: The default timeout is 600 seconds. You can increase this for a specific job by adding a header:

http
    timeout: 1200

3. Load Balance Across FEs If all 6 NiFi nodes are pointing to a single FE IP, you may be hitting a bottleneck at the FE or causing a "thundering herd" on a single BE (since the FE redirects the request). * Best Practice: Use a load balancer (like F5, HAProxy, or Nginx) in front of your FE nodes. This distributes the initial connections. * Alternative: Hardcode different FE IPs across your 6 NiFi nodes so they don't all hit the same leader FE for the initial handshake. 4. Tune Concurrent Transaction Limits StarRocks has limits on how many concurrent transactions a single BE can handle. *

stream_load_max_txn_num_per_be

: (Introduced in v3.3.0) If this is set, a BE might reject new loads if it's already busy. * Check your FE logs for

slow db lock

or

THRIFT_EAGAIN

. If you see these, it confirms that staggering would help, but Merge Commit (Solution 1) is the better long-term fix. Should you stagger? If you cannot upgrade to v3.4+ or adjust the configurations above, then yes, staggering by a few seconds or using a NiFi "ControlRate" processor to limit concurrent executions can prevent the "all-at-once" lock contention. However, try the Merge Commit header first as it is much more performant. References • administration/management/FE_configuration.md • loading/StreamLoad.md • administration/management/BE_configuration.md • faq/loading/Stream_load_faq.md

@Rocky the docs say not to use merge commit if it's not concurrent and it won't always be concurrent, should I avoid?

The recommendation to avoid Merge Commit for single-concurrency loads is primarily about latency, not safety. Here is how to decide based on your specific NiFi setup: Why the docs say "avoid if not concurrent" When you enable Merge Commit, StarRocks opens a "merging window" (defined by

merge_commit_interval_ms

). Even if only one NiFi node sends a request, the server will wait for that entire window to expire before committing the data and returning a "success" response to NiFi. * If you set a 5-second window: A single load that normally takes 200ms will now take 5+ seconds. * If you have 6 nodes: In your current "thundering herd" scenario where they hit at once, Merge Commit is exactly what you need to prevent timeouts and "too many versions" errors. Should you use it anyway? Yes, if your primary problem is the "at the same time" timeouts. The trade-off is simply that your NiFi processors will spend more time in a "Running" state waiting for the HTTP response when the traffic is low. Use Merge Commit if: 1. Timeouts are your biggest pain point: It is better for a single load to take 5 seconds than for concurrent loads to fail or cause cluster-wide transaction lock contention. 2. You can tolerate the latency: If NiFi doesn't care that a single job takes a few extra seconds to complete, there is no technical reason to avoid it. 3. Your requests are "homogeneous": All 6 nodes must use the exact same HTTP headers (same columns, same format, same merge parameters). If the headers differ, they won't be merged. The "Staggering" Alternative If you decide to avoid Merge Commit and prefer to stagger your NiFi nodes: * NiFi Solution: Use a ControlRate processor before the

InvokeHTTP

to limit the number of concurrent loads to 1 or 2 across the cluster, or use a "Random Delay" in your flow. * StarRocks side: This will result in 6 separate transactions. While this avoids the timeout, it creates 6 different data versions in a short window. If this NiFi process runs frequently (e.g., every minute), you might eventually hit "too many versions" (compaction) issues. Summary Recommendation If you are on v3.4.0+, try Merge Commit with a short interval (e.g.,

merge_commit_interval_ms: 1000

or

2000

). * Benefit: 100% protection against the 6-node concurrency timeout. * Cost: At low traffic, each NiFi task will wait 1–2 seconds for a response. Warning: Note that with Merge Commit, if one of the 6 concurrent requests has a data quality error (e.g., a string in an integer column), the entire merged transaction (data from all 6 nodes) will fail. References • loading/StreamLoad.md • sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md • loading/Flink-connector-starrocks.md • faq/loading/Stream_load_faq.md References • loading/StreamLoad.md • sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md • loading/Flink-connector-starrocks.md

@Rocky what should i set merge_commit_parallel to ?

For your 6-node NiFi setup, you should typically set

merge_commit_parallel

to a value between 1 and 3, or match your number of BE nodes if you are pushing a high volume of data. Here is how to choose the specific value: 1. The "Rule of Thumb" * Small Data (KB to few MBs per NiFi node): Set it to 1. If the total merged data in one window is small, a single-thread plan is more efficient as it avoids the overhead of distributing the task across BEs. * Medium/Large Data (Tens of MBs per window): Set it to 2 or 3. This is the default in many StarRocks connectors (like Flink) and provides a good balance. * Max Limit: StarRocks will automatically cap this value at your actual number of BE nodes (

min(merge_commit_parallel, BE_count)

). If you have 3 BEs, setting it to 10 will still only use 3. 2. How it works

merge_commit_parallel

controls how many BE nodes StarRocks uses to actually process the data after it has collected all the small files from your 6 NiFi nodes into a single transaction. * It does not limit how many NiFi nodes can connect. All 6 NiFi nodes can still send data simultaneously. * It does determine how many parallel "streams" the cluster uses to write that combined data to the tablets. 3. Recommended Headers for NiFi If you are moving to Merge Commit to solve your timeout issues, use these settings in your

InvokeHTTP

processor: *

enable_merge_commit: true

*

merge_commit_interval_ms: 1000

(Collects all NiFi hits within 1 second. Increase to 3000-5000 if your NiFi nodes are slightly staggered). *

merge_commit_parallel: 2

(A safe starting point for most clusters). *

merge_commit_async: false

(Keep this

false

so NiFi waits for the "Success" confirmation before moving the flowfile to the next processor). Summary If you just want it to work without deep tuning, set

merge_commit_parallel: 2

. It is high enough to utilize your cluster's resources but low enough to avoid unnecessary management overhead for what are likely relatively small individual NiFi bundles. References • sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md • loading/Flink-connector-starrocks.md • loading/StreamLoad.md • faq/loading/Stream_load_faq.md References • sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md • loading/Flink-connector-starrocks.md • loading/StreamLoad.md

@Rocky i'm dynamically creating the url for the stream load based on the data, is this a bad place to use merge_commit?

Using a dynamic URL (where the database or table name changes) with Merge Commit can be tricky. Whether it is a "bad" place depends on how many different tables you are hitting and whether the load parameters change along with the URL. Here are the three critical constraints you need to consider: 1. Merging only happens per table StarRocks can only merge requests that are heading to the exact same database and table. * If NiFi Node 1 and Node 2 both hit

table_A

at the same time, they will be merged. * If Node 1 hits

table_A

and Node 2 hits

table_B

, they will not be merged. They will run as two separate, independent transactions. * Result: If your "dynamic" logic means each NiFi node is usually hitting a different table, Merge Commit won't solve your concurrency problem. 2. The "Homogeneous" Requirement For requests to be merged, all HTTP headers (parameters) must be identical. * If you are dynamically changing the

columns

header or

jsonpaths

based on the data, StarRocks will treat them as different groups. * Requests with different

column_separator

,

where

clauses, or even different

merge_commit_interval_ms

values will not be merged together, even if they hit the same table. 3. Resource Overhead (The "Too Many Tables" Risk) If your dynamic URL logic hits hundreds of different tables and you enable Merge Commit for all of them: * The StarRocks BE (Backend) has to maintain an active "merging window" (a memory buffer and a timer) for every unique table currently receiving data. * If you have a very high number of tables, this can increase memory consumption and management overhead on the BEs. Recommendations * If you hit the same few tables frequently: Merge Commit is still a great choice. It will handle the "thundering herd" whenever multiple nodes happen to target the same table. * If you hit hundreds of different tables: Avoid Merge Commit. The transaction lock contention is usually only a problem when many clients hit the same table. If your NiFi nodes are naturally spread out across many different tables, they are unlikely to block each other anyway. * Check your Parameters: Ensure that for any given table, all NiFi nodes are using the exact same load headers. If Node A uses

columns: id, name

and Node B uses

columns: name, id

, they will not merge. Summary: It’s not "bad," but it is ineffective if your dynamic logic prevents requests from being "homogeneous" or if it spreads the load across so many tables that they never actually collide. If your goal is just to stop the timeouts and you have many tables, simply increasing the HTTP timeout in NiFi and StarRocks is often a safer first step than Merge Commit. References • loading/StreamLoad.md • sql-reference/sql-statements/loading_unloading/STREAM_LOAD.md • loading/Flink-connector-starrocks.md • faq/loading/Stream_load_faq.md References • loading/Flink-connector-starrocks.md • loading/StreamLoad.md • faq/Sql_faq.md