{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:VJZZW2N2KX5DPD2QI7VJIAEJO5","short_pith_number":"pith:VJZZW2N2","canonical_record":{"source":{"id":"2403.14902","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2024-03-22T01:17:07Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"9d43de67096945c237c8bae9544c07b2ef93eb1e5c98a80044204c7cacd87117","abstract_canon_sha256":"b269e3fa4d2efd7bf1d9e54fa28fc5a1c16237a22135a2ba7282447c15b3ad09"},"schema_version":"1.0"},"canonical_sha256":"aa739b69ba55fa378f5047ea94008977722f4c1ea84e1926457878a75ab1abe3","source":{"kind":"arxiv","id":"2403.14902","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.14902","created_at":"2026-07-05T07:59:27Z"},{"alias_kind":"arxiv_version","alias_value":"2403.14902v1","created_at":"2026-07-05T07:59:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.14902","created_at":"2026-07-05T07:59:27Z"},{"alias_kind":"pith_short_12","alias_value":"VJZZW2N2KX5D","created_at":"2026-07-05T07:59:27Z"},{"alias_kind":"pith_short_16","alias_value":"VJZZW2N2KX5DPD2Q","created_at":"2026-07-05T07:59:27Z"},{"alias_kind":"pith_short_8","alias_value":"VJZZW2N2","created_at":"2026-07-05T07:59:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:VJZZW2N2KX5DPD2QI7VJIAEJO5","target":"record","payload":{"canonical_record":{"source":{"id":"2403.14902","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2024-03-22T01:17:07Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"9d43de67096945c237c8bae9544c07b2ef93eb1e5c98a80044204c7cacd87117","abstract_canon_sha256":"b269e3fa4d2efd7bf1d9e54fa28fc5a1c16237a22135a2ba7282447c15b3ad09"},"schema_version":"1.0"},"canonical_sha256":"aa739b69ba55fa378f5047ea94008977722f4c1ea84e1926457878a75ab1abe3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:59:27.512864Z","signature_b64":"FCA4IxLkCSM705w0ZqpWlgS/YYrEP62bZTdDhzJWZdwZT3okic10mjwAM+N/KIGgExF9UL7oCCWFEQPmofyOAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aa739b69ba55fa378f5047ea94008977722f4c1ea84e1926457878a75ab1abe3","last_reissued_at":"2026-07-05T07:59:27.512348Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:59:27.512348Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.14902","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:59:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5N869U6PxiFOQbY4DjmguN9fn0Kqzw6hi/CzJe1h6W0Fxyg7KTKMAhjaqU4oGO0XEUZxae692QXtMylWAG4LDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T16:21:46.873183Z"},"content_sha256":"a7463140ef743aed492f810167ce1f5c8190b05c16cd5a34e04d704db51c7668","schema_version":"1.0","event_id":"sha256:a7463140ef743aed492f810167ce1f5c8190b05c16cd5a34e04d704db51c7668"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:VJZZW2N2KX5DPD2QI7VJIAEJO5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hydro: Adaptive Query Processing of ML Queries","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.DB","authors_text":"Aubhro Sengupta, Gaurav Tarlok Kakkar, Hyesoon Kim, Jiashen Cao, Joy Arulraj","submitted_at":"2024-03-22T01:17:07Z","abstract_excerpt":"Query optimization in relational database management systems (DBMSs) is critical for fast query processing. The query optimizer relies on precise selectivity and cost estimates to effectively optimize queries prior to execution. While this strategy is effective for relational DBMSs, it is not sufficient for DBMSs tailored for processing machine learning (ML) queries. In ML-centric DBMSs, query optimization is challenging for two reasons. First, the performance bottleneck of the queries shifts to user-defined functions (UDFs) that often wrap around deep learning models, making it difficult to a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.14902","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2403.14902/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:59:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p69jzirIpVY4+WzAqz9d5Bubp4SLQMNhMuzHfAFIZQjQEazfUP63O/JYYlKG65g0aIpzt3Lgl4JCdacdKjdvBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T16:21:46.873698Z"},"content_sha256":"8d55a0ae44d14a68551a503ff0a6fc6fbe3fc5b16e550c3793d87b82dd09e9d0","schema_version":"1.0","event_id":"sha256:8d55a0ae44d14a68551a503ff0a6fc6fbe3fc5b16e550c3793d87b82dd09e9d0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VJZZW2N2KX5DPD2QI7VJIAEJO5/bundle.json","state_url":"https://pith.science/pith/VJZZW2N2KX5DPD2QI7VJIAEJO5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VJZZW2N2KX5DPD2QI7VJIAEJO5/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-08T16:21:46Z","links":{"resolver":"https://pith.science/pith/VJZZW2N2KX5DPD2QI7VJIAEJO5","bundle":"https://pith.science/pith/VJZZW2N2KX5DPD2QI7VJIAEJO5/bundle.json","state":"https://pith.science/pith/VJZZW2N2KX5DPD2QI7VJIAEJO5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VJZZW2N2KX5DPD2QI7VJIAEJO5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:VJZZW2N2KX5DPD2QI7VJIAEJO5","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"b269e3fa4d2efd7bf1d9e54fa28fc5a1c16237a22135a2ba7282447c15b3ad09","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2024-03-22T01:17:07Z","title_canon_sha256":"9d43de67096945c237c8bae9544c07b2ef93eb1e5c98a80044204c7cacd87117"},"schema_version":"1.0","source":{"id":"2403.14902","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.14902","created_at":"2026-07-05T07:59:27Z"},{"alias_kind":"arxiv_version","alias_value":"2403.14902v1","created_at":"2026-07-05T07:59:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.14902","created_at":"2026-07-05T07:59:27Z"},{"alias_kind":"pith_short_12","alias_value":"VJZZW2N2KX5D","created_at":"2026-07-05T07:59:27Z"},{"alias_kind":"pith_short_16","alias_value":"VJZZW2N2KX5DPD2Q","created_at":"2026-07-05T07:59:27Z"},{"alias_kind":"pith_short_8","alias_value":"VJZZW2N2","created_at":"2026-07-05T07:59:27Z"}],"graph_snapshots":[{"event_id":"sha256:8d55a0ae44d14a68551a503ff0a6fc6fbe3fc5b16e550c3793d87b82dd09e9d0","target":"graph","created_at":"2026-07-05T07:59:27Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2403.14902/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Query optimization in relational database management systems (DBMSs) is critical for fast query processing. The query optimizer relies on precise selectivity and cost estimates to effectively optimize queries prior to execution. While this strategy is effective for relational DBMSs, it is not sufficient for DBMSs tailored for processing machine learning (ML) queries. In ML-centric DBMSs, query optimization is challenging for two reasons. First, the performance bottleneck of the queries shifts to user-defined functions (UDFs) that often wrap around deep learning models, making it difficult to a","authors_text":"Aubhro Sengupta, Gaurav Tarlok Kakkar, Hyesoon Kim, Jiashen Cao, Joy Arulraj","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2024-03-22T01:17:07Z","title":"Hydro: Adaptive Query Processing of ML Queries"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.14902","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:a7463140ef743aed492f810167ce1f5c8190b05c16cd5a34e04d704db51c7668","target":"record","created_at":"2026-07-05T07:59:27Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"b269e3fa4d2efd7bf1d9e54fa28fc5a1c16237a22135a2ba7282447c15b3ad09","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2024-03-22T01:17:07Z","title_canon_sha256":"9d43de67096945c237c8bae9544c07b2ef93eb1e5c98a80044204c7cacd87117"},"schema_version":"1.0","source":{"id":"2403.14902","kind":"arxiv","version":1}},"canonical_sha256":"aa739b69ba55fa378f5047ea94008977722f4c1ea84e1926457878a75ab1abe3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aa739b69ba55fa378f5047ea94008977722f4c1ea84e1926457878a75ab1abe3","first_computed_at":"2026-07-05T07:59:27.512348Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:59:27.512348Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FCA4IxLkCSM705w0ZqpWlgS/YYrEP62bZTdDhzJWZdwZT3okic10mjwAM+N/KIGgExF9UL7oCCWFEQPmofyOAw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:59:27.512864Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.14902","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a7463140ef743aed492f810167ce1f5c8190b05c16cd5a34e04d704db51c7668","sha256:8d55a0ae44d14a68551a503ff0a6fc6fbe3fc5b16e550c3793d87b82dd09e9d0"],"state_sha256":"b813cb8d6effd1a0764ac784d0756bb663011dca357932713ff156ca707b14cf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ppmF3wfLHOwffuiTjp2Md7nYyiBWLuZ7vI/Exown9EqzAbMhST8wN0vHavgcUm8QCE/CAEZKsEKuLQcZ9ajDDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T16:21:46.881558Z","bundle_sha256":"e331094374ec78794840cc7b0d5f5ef6ca52077d5513ca2c5f51adf22c0d9e98"}}