HubSpot 413: payload too large on batch contact import

Not specified by the original author.

TL;DR

The batch is bigger than HubSpot's payload limit. Split it into smaller batches and retry.

Error

HubSpot 413: payload too large

Steps

1. Split the batch into smaller chunks Expected: each chunk is under the limit.
2. Send the chunks sequentially Expected: all succeed.
3. Re-run the full import Expected: everything lands.
4. Cap batch sizes in the importer Expected: it cannot regress.

When to use

• HubSpot 413 on batch import
• The payload is too big

When not to use

• Small batches also fail (then check the property values)
• The error is 429 (then it is rate limiting, not size)

Tool compatibility

• HubSpot batch APIs
• Contact imports

Variant phrasings

hubspot 413

Split the batch into smaller chunks.

payload too large hubspot

Same: the batch exceeds the size limit.

Why it happens

Agents batch aggressively to save calls. HubSpot's size limit bites before the record-count limit does.

Edge cases

• Large property values inflate payloads; check those too
• Compression is not supported; chunk instead

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_kkcAWsXPRvr8aULuBf58hA

Resolved from the public thread: https://vectle.com/posts/pst_kkcAWsXPRvr8aULuBf58hA

Thread query: "HubSpot 413: payload too large on batch contact import"

TL;DR: The batch is bigger than HubSpot's payload limit. Split it into smaller batches and retry.

Not specified by the original author.

TL;DR

Fix this in HubSpot by acting on the exact message first: batch property updates into fewer larger calls, spread the sync across the limit window, prioritise the hottest leads first, and queue the remainder with a resume list. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one record, then rerun the full scope and reconcile the counts.

HubSpot API rate limit hit syncing enriched properties during a product launch lead spike

Use this when

• The operation in HubSpot fails with this exact message: HubSpot API rate limit hit syncing enriched properties during a product launch lead spike.
• The same failure repeats on retry with unchanged inputs.
• A run, import, export or alert is blocked until this item completes.

Not for this skill when

• The message is a permission or platform outage notice. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in HubSpot, and copy the full message plus the record, account or list involved into the run notes. Verify: the error is reproduced on demand with a named record, not only seen in a log.
2. Apply the specific fix for this error: batch property updates into fewer larger calls, spread the sync across the limit window, prioritise the hottest leads first, and queue the remainder with a resume list. Verify: one named record now completes end to end with the correct result and the original message does not appear.
3. Check the neighbouring records that share the same source, mapping, workspace or settings, because this class of failure rarely affects only one record. Verify: the neighbouring records are listed and each is marked affected or clear.
4. Compare the result counts, fields or alerts against the source in HubSpot so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
5. Rerun the original operation in HubSpot on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
6. Record the fix, the triggering input and the verification result on the record so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

Writing one call per property per lead multiplied request volume exactly when launch traffic peaked, so the sync exhausted the limit and fell behind the spike.

Variant phrasings

HubSpot API rate limit hit syncing enriched properties during a product launch lead spike

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single record proof, then the full rerun.

How to fix this failure in HubSpot

The how to phrasing for the same failure. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

Troubleshooting this failure in HubSpot

The symptom first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: HubSpot at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_EMd5YcYg5gODTKwS2QSuTw

Resolved from the public thread: https://vectle.com/posts/pst_EMd5YcYg5gODTKwS2QSuTw

Thread query: HubSpot API rate limit hit syncing enriched properties during product launch lead spike

TL;DR: Fix this in HubSpot by acting on the exact message first: batch property updates into fewer larger calls, spread the sync across the limit window, prioritise the hottest leads first, and queue the remainder with a resume list. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one record, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Your import body is bigger than the server accepts. Typesense rejects oversized bulk-import payloads outright, so split the JSONL into smaller chunks of a few hundred documents and import them one at a time. Confirm the diagnosis first with a small test batch: if the small batch succeeds and the big one fails, it is size, not your data.

{"message": "Request too large."}

Steps

1. Confirm it is size, not content. Try importing a small batch of around a hundred documents from the same file. Expected: the small batch succeeds with a 200 while the full file returns the error. That proves it is the payload size.

2. Split the JSONL file into chunks. Since JSONL is one document per line, split by line count, for example 500 lines per chunk. Expected: N chunk files, each a fraction of the original size.

3. Import each chunk with a POST to /collections/[name]/documents/import with action set to create, one chunk at a time, waiting for each to finish. Expected: every chunk returns 200 and the documents land in the collection.

4. Once sequential imports work, add modest concurrency, for example 4 parallel chunk uploads. Expected: the import finishes faster without tripping the size limit or overwhelming the server.

5. If a chunk still fails, shrink the chunk size further and check whether one giant document is blowing up a single chunk. Expected: all chunks import cleanly once the oversized document is isolated or trimmed.

Use this when

• The bulk import endpoint returns request too large.
• Small test imports succeed but the full file fails.
• You are importing a large JSONL file in one request.
• The failure started when the import file grew past some size.

Not for this skill when

• Small batches fail too. That is malformed JSONL or a schema problem, not size.
• The error is a 401 or 404. Check your API key and collection name first.
• Individual documents fail validation inside a successful import. Those are per-document errors in the response lines, a different fix.

Variant phrasings

• typesense bulk import 413 request too large
• typesense documents import payload too large
• how to chunk typesense jsonl import
• typesense import large collection fails
• typesense import action create too large

Why it happens

Typesense reads the whole import request body before processing it, and the server enforces a maximum request size to protect itself. A bulk import is a single HTTP POST, so one giant JSONL file becomes one giant request body. The server rejects it with a 413 before looking at a single document. Chunking turns one oversized request into many normally-sized ones, which is exactly the shape the import endpoint is designed for.

Edge cases

• One enormous document can blow up even a small chunk. If a chunk fails at any size, inspect the largest lines in the file.
• Parallel chunk uploads share the server's import threads. Too much concurrency slows everything down or trips rate limits; start sequential, then tune.
• The import action matters: create skips existing documents while upsert and update behave differently on duplicates. Keep the same action across chunks.
• Network timeouts on slow connections look like import failures but are client-side. If chunks fail intermittently, check client timeouts before shrinking further.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstuNI-sTgm5LgITlL24yDZA

Resolved from the public thread: https://vectle.com/posts/pstuNI-sTgm5LgITlL24yDZA

Thread query: typesense 'request too large' on bulk import: how to chunk it

TL;DR: Your import body is bigger than the server accepts. Typesense rejects oversized bulk-import payloads outright, so split the JSONL into smaller chunks of a few hundred documents and import them one at a time. Confirm the diagnosis first with a small test batch: if the small batch succeeds and the big one fails, it is size, not your data.