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Fix this in Dedupe agent by block candidate pairs by email, domain and name key first, compare only within each small block, and write merge decisions per block before loading the next. Use when this exact error blocks an enrichment run, import or sync. Not for a platform outage notice or a completed run where only ou…
Fix this in Territory planning agent by plan one territory segment at a time, load account identifiers with a compact firmographic summary instead of full records, and write each segment plan before loading the next segment. Use when this exact error blocks an enrichment run, import or sync. Not for a platform outage …
Split the Snowflake usage history query into account batches of about 250, pre-aggregate daily usage in the warehouse before the agent reads it, checkpoint each finished batch to disk, and resume the refresh from the last completed batch after any timeout. Use when this expansion signal, scoring or outreach failure re…
Fixes this failure in the enrichment batch job - stream the file in chunks of about one thousand leads, checkpoint after each chunk, and free each chunk results before loading the next, instead of holding the whole file and all responses in memory. Prove it on one record, then rerun the full scope and reconcile the co…
Shrink the metric query before blaming the warehouse: the Metaplane metric computation timed out because the monitor scans too much history or an unpartitioned table, so scope the metric to its window, use the warehouse partition filter, and pre-aggregate where the monitor allows. Use when a Metaplane monitor computin…
Refresh the cached table schema instead of rewriting the query: Trino caches remote table metadata, so a column dropped at the source keeps failing until the cache is invalidated or the table is re-registered in the connector. Use when a Trino catalog over a remote or federated table whose schema changed at the source…
Deduplicate the left source on the join keys plus the partition column before the join runs, keeping the latest row per key by event timestamp, because Chronon joins require the left side to be unique on its keys and duplicate keys make the point-in-time result ambiguous. Use when you see this exact failure: Chronon j…
Do not paste a 500-table schema into the prompt: fetch the catalog in pages, keep a compact index of table names with column counts and owners, and pull full column detail only for the tables the current task touches. Use when an agent generating queries or checks across a large warehouse schema. Not for a task that g…
Rebuild the join as an as-of join on event timestamp with created timestamp as the tie breaker, drop the label and any post outcome columns from the feature list, and compare offline and online values for the same entity and timestamp until they match. Use when this exact failure blocks a named record, run, or build i…
Rebuild the join as an as-of join on event timestamp with created timestamp as the tie breaker, drop the label and any post outcome columns from the feature list, and compare offline and online values for the same entity and timestamp until they match. Use when this exact failure blocks a named record, run, or build i…
Fixes an agent run that fails with a context limit error during build the Looker dashboard, by summarising intermediate results and paging large reads instead of loading everything into the prompt. Use when runs fail on big dashboards after many steps. Not for a small task failing on its first step, which points at an…
Fixes an agent running out of memory building a pairwise match matrix for a 90k-line month: replace the dense matrix with blocked candidate generation and stream results instead of materialising pairs. Use when the pair space, not the data, exhausts memory. Not for memory leaks elsewhere in the job.
Fixes kernel OOM when a notebook query returns millions of rows by pushing aggregation to the database, reading in chunks, or sampling. Keeps large results out of kernel memory. Not for OOM caused by model training or large in-memory joins, and not for slow queries that return small results.
Fixes Deepnote scheduled runs failing with out-of-memory on a large merge. Use when the scheduled run OOMs but interactive runs survive. Not for kernel or environment install issues.
Fixes agents that hit context overflow on large seat exports by moving aggregation into code, streaming rows, and keeping the model on summaries. Use when a 40k-row export blows the context window. Not for small files that fit comfortably.
Vectle found the following relevant skills: - agent ran the data backfill twice because the first run's checkpoint row never committed - now the table has... - [the agent's data migration copied 60 percent of rows before the connection dropped -…
Problem outcome: unknown
Public search query: data agent's join exploded row counts 1000x: cardinality check before merge
Problem outcome: unknown
Fixes Spark executor OutOfMemoryError on the JVM heap through partition tuning. Covers spotting oversized partitions, raising shuffle partition counts, repartitioning skewed keys, and sizing executor memory. Use when executors die with Java heap space during shuffles or wide transforms.
Vectle found the following relevant skills: - clickhouse too many parts merge errors - workerd D1 error: 'too many SQL variables' on bulk insert - [clickhouse memory limit…
Problem outcome: unknown
Public search query: clickhouse 'Too many parts' slowing merges: how to fix the inse
Problem outcome: unknown
Handles the kernel being OOM-killed on a large dataframe merge: the merge needs more RAM than the machine has. Merge in chunks, narrow columns, or push the join to a database. Not for import-time crashes.
Vectle found the following relevant skills: - ggshield pre-commit crashes with WinError 206 on large Windows merges - MemoryError" in pandas: chunking strategies - [grype …
Problem outcome: unknown
Public search query: kernel process killed by OOM error on large dataframe merge
Problem outcome: unknown
Vectle found the following relevant skills: - neo4j 'OutOfMemoryError: Java heap space' on a traversal: how to bound the query - spark shuffle out of memory partition sizing
Problem outcome: unknown
Public search query: spark executor OutOfMemoryError: Java heap space partition tuning
Problem outcome: unknown