Parallel Execution
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Parallel Execution has 11 facts recorded in Dontopedia across 3 references, with 2 live disagreements.
Mostly:describes(3), rdf:type(2), contains function(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (4)
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complementsComplements(1)
- Batch Processing Section
ex:batch-processing-section
contextContext(1)
- Thread Pool Executor
ex:thread-pool-executor
describedInDescribed in(1)
- Process Texts in Parallel Function
ex:process-texts-in-parallel-function
followsFollows(1)
- Memory Profiling Section
ex:memory-profiling-section
Other facts (9)
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| Predicate | Value | Ref |
|---|---|---|
| Describes | handle_queries method uses ThreadPoolExecutor | [2] |
| Describes | batch_process_queries processes queries in batches | [2] |
| Describes | Thread Pool Executor | [3] |
| Rdf:type | Documentation Section | [1] |
| Rdf:type | Section | [3] |
| Contains Function | Process Texts in Parallel Function | [1] |
| Enables | Concurrent Processing | [3] |
| Sub Item | 3 | [3] |
| Benefit | Concurrent Processing | [3] |
Timeline
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References (3)
ctx:claims/beam/449c3497-7bf6-4f4c-9327-9e55d9760075- full textbeam-chunktext/plain1 KB
doc:beam/449c3497-7bf6-4f4c-9327-9e55d9760075Show excerpt
4. **Batch Processing**: - Define `process_batch` to process a batch of texts using `nlp.pipe`. 5. **Parallel Execution**: - Define `process_texts_in_parallel` to process texts in parallel using `ThreadPoolExecutor`. - Split the t…
ctx:claims/beam/a1c7ec7f-b733-4cc2-b1dc-07783fabac2c- full textbeam-chunktext/plain1 KB
doc:beam/a1c7ec7f-b733-4cc2-b1dc-07783fabac2cShow excerpt
queries = ["query1", "query2", "query3"] * 500 # 1500 queries start_time = time.time() rewritten_queries = rewriter.batch_process_queries(queries) end_time = time.time() print(f"Processed {len(rewritten_queries)} queries in {end_time - st…
ctx:claims/beam/cac1c21a-0e1f-4151-8a07-01d4a78fd51c- full textbeam-chunktext/plain1 KB
doc:beam/cac1c21a-0e1f-4151-8a07-01d4a78fd51cShow excerpt
for future in as_completed(futures): results.extend(future.result()) return results # Example usage: queries = ["What is the capital of France?", "Who is the president of the United States?", ...] reformulated_q…
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