GraphRAG performance enhacements #924
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Signed-off-by: Rita Brugarolas <[email protected]>
for more information, see https://pre-commit.ci
…o directly run build communities Signed-off-by: Rita Brugarolas <[email protected]>
for more information, see https://pre-commit.ci
Signed-off-by: Rita Brugarolas <[email protected]>
Signed-off-by: Rita Brugarolas <[email protected]>
for more information, see https://pre-commit.ci
Signed-off-by: Rita Brugarolas <[email protected]>
Signed-off-by: rbrygaro <[email protected]>
for more information, see https://pre-commit.ci
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There are lot of dataprep backends and neoj4/llama is not the default one used in docker compose files and Helm charts. Do the ones used by default have also similar bottleneck? |
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Issue: When property graph store gets filled (~12K nodes, 15K relationships) insertion time in dataprep gets slow.
Extraction + insertion starts at ~30 sec and once it gets filled grows to (~12K nodes, 15K relationships) ~800 sec
Perf bottleneck this cypher call in llama-index to do node upsert:
https://github.com/run-llama/llama_index/blob/795bebc2bad31db51b854a5c062bedca42397630/llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/neo4j_property_graph.py#L334
WIP solution: