{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:SI3DVNNTUCUG3WLGRIXF6RI6OS","short_pith_number":"pith:SI3DVNNT","canonical_record":{"source":{"id":"1808.03196","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2018-08-09T15:30:06Z","cross_cats_sorted":[],"title_canon_sha256":"027291070952bd0927ade2f2ba8cf51695e692b39d0837f5718e72e9848f9708","abstract_canon_sha256":"caf7590eda413c3a51dd0a9688c50a4e9608e43943eb3b2a5aed10a6fd86b42d"},"schema_version":"1.0"},"canonical_sha256":"92363ab5b3a0a86dd9668a2e5f451e74b3e630d9b8d876fd184697450314855a","source":{"kind":"arxiv","id":"1808.03196","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.03196","created_at":"2026-05-17T23:56:33Z"},{"alias_kind":"arxiv_version","alias_value":"1808.03196v2","created_at":"2026-05-17T23:56:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.03196","created_at":"2026-05-17T23:56:33Z"},{"alias_kind":"pith_short_12","alias_value":"SI3DVNNTUCUG","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"SI3DVNNTUCUG3WLG","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"SI3DVNNT","created_at":"2026-05-18T12:32:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:SI3DVNNTUCUG3WLGRIXF6RI6OS","target":"record","payload":{"canonical_record":{"source":{"id":"1808.03196","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2018-08-09T15:30:06Z","cross_cats_sorted":[],"title_canon_sha256":"027291070952bd0927ade2f2ba8cf51695e692b39d0837f5718e72e9848f9708","abstract_canon_sha256":"caf7590eda413c3a51dd0a9688c50a4e9608e43943eb3b2a5aed10a6fd86b42d"},"schema_version":"1.0"},"canonical_sha256":"92363ab5b3a0a86dd9668a2e5f451e74b3e630d9b8d876fd184697450314855a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:33.661864Z","signature_b64":"PtajnUMlOw4ffqlivCtqaCbU1oESaohsyCjY7TtrU2b9ZH7PcbxpUrS+kgQOHdh5PzVzFdlkahCGdA0vMUVEAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"92363ab5b3a0a86dd9668a2e5f451e74b3e630d9b8d876fd184697450314855a","last_reissued_at":"2026-05-17T23:56:33.660963Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:33.660963Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.03196","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:56:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GTdbIc77H550Nge/uhQAVdOCcwVhr++7vEcfVIsGX2WAj63wZzKiFMuZGikY07p3DSnFUFArvEGsAWcx6+GKBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T09:25:36.415467Z"},"content_sha256":"e0b05790c2a31c11a5fd95542229dd5080006ef18602f5bb6d206b4c395997aa","schema_version":"1.0","event_id":"sha256:e0b05790c2a31c11a5fd95542229dd5080006ef18602f5bb6d206b4c395997aa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:SI3DVNNTUCUG3WLGRIXF6RI6OS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning to Optimize Join Queries With Deep Reinforcement Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Ion Stoica, Joseph Hellerstein, Ken Goldberg, Sanjay Krishnan, Zongheng Yang","submitted_at":"2018-08-09T15:30:06Z","abstract_excerpt":"Exhaustive enumeration of all possible join orders is often avoided, and most optimizers leverage heuristics to prune the search space. The design and implementation of heuristics are well-understood when the cost model is roughly linear, and we find that these heuristics can be significantly suboptimal when there are non-linearities in cost. Ideally, instead of a fixed heuristic, we would want a strategy to guide the search space in a more data-driven way---tailoring the search to a specific dataset and query workload. Recognizing the link between classical Dynamic Programming enumeration met"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.03196","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-17T23:56:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q2A7wTgsj5y++EnVBN/KOZJXHWzCnU+3W4Ei71Nc0nmoc/QuvpjznpHOMWeOE0Oq43NdLLZG1e/8YEWX4Zi1Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T09:25:36.415935Z"},"content_sha256":"e59668dcd100d48b878fc9bf09383a6e75424d10aad27e14ec2b62444a5cc742","schema_version":"1.0","event_id":"sha256:e59668dcd100d48b878fc9bf09383a6e75424d10aad27e14ec2b62444a5cc742"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SI3DVNNTUCUG3WLGRIXF6RI6OS/bundle.json","state_url":"https://pith.science/pith/SI3DVNNTUCUG3WLGRIXF6RI6OS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SI3DVNNTUCUG3WLGRIXF6RI6OS/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":"2026-08-09T09:25:36Z","links":{"resolver":"https://pith.science/pith/SI3DVNNTUCUG3WLGRIXF6RI6OS","bundle":"https://pith.science/pith/SI3DVNNTUCUG3WLGRIXF6RI6OS/bundle.json","state":"https://pith.science/pith/SI3DVNNTUCUG3WLGRIXF6RI6OS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SI3DVNNTUCUG3WLGRIXF6RI6OS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:SI3DVNNTUCUG3WLGRIXF6RI6OS","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":"caf7590eda413c3a51dd0a9688c50a4e9608e43943eb3b2a5aed10a6fd86b42d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2018-08-09T15:30:06Z","title_canon_sha256":"027291070952bd0927ade2f2ba8cf51695e692b39d0837f5718e72e9848f9708"},"schema_version":"1.0","source":{"id":"1808.03196","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.03196","created_at":"2026-05-17T23:56:33Z"},{"alias_kind":"arxiv_version","alias_value":"1808.03196v2","created_at":"2026-05-17T23:56:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.03196","created_at":"2026-05-17T23:56:33Z"},{"alias_kind":"pith_short_12","alias_value":"SI3DVNNTUCUG","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"SI3DVNNTUCUG3WLG","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"SI3DVNNT","created_at":"2026-05-18T12:32:53Z"}],"graph_snapshots":[{"event_id":"sha256:e59668dcd100d48b878fc9bf09383a6e75424d10aad27e14ec2b62444a5cc742","target":"graph","created_at":"2026-05-17T23:56:33Z","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"},"paper":{"abstract_excerpt":"Exhaustive enumeration of all possible join orders is often avoided, and most optimizers leverage heuristics to prune the search space. The design and implementation of heuristics are well-understood when the cost model is roughly linear, and we find that these heuristics can be significantly suboptimal when there are non-linearities in cost. Ideally, instead of a fixed heuristic, we would want a strategy to guide the search space in a more data-driven way---tailoring the search to a specific dataset and query workload. Recognizing the link between classical Dynamic Programming enumeration met","authors_text":"Ion Stoica, Joseph Hellerstein, Ken Goldberg, Sanjay Krishnan, Zongheng Yang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2018-08-09T15:30:06Z","title":"Learning to Optimize Join Queries With Deep Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.03196","kind":"arxiv","version":2},"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:e0b05790c2a31c11a5fd95542229dd5080006ef18602f5bb6d206b4c395997aa","target":"record","created_at":"2026-05-17T23:56:33Z","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":"caf7590eda413c3a51dd0a9688c50a4e9608e43943eb3b2a5aed10a6fd86b42d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2018-08-09T15:30:06Z","title_canon_sha256":"027291070952bd0927ade2f2ba8cf51695e692b39d0837f5718e72e9848f9708"},"schema_version":"1.0","source":{"id":"1808.03196","kind":"arxiv","version":2}},"canonical_sha256":"92363ab5b3a0a86dd9668a2e5f451e74b3e630d9b8d876fd184697450314855a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"92363ab5b3a0a86dd9668a2e5f451e74b3e630d9b8d876fd184697450314855a","first_computed_at":"2026-05-17T23:56:33.660963Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:56:33.660963Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PtajnUMlOw4ffqlivCtqaCbU1oESaohsyCjY7TtrU2b9ZH7PcbxpUrS+kgQOHdh5PzVzFdlkahCGdA0vMUVEAQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:56:33.661864Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.03196","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e0b05790c2a31c11a5fd95542229dd5080006ef18602f5bb6d206b4c395997aa","sha256:e59668dcd100d48b878fc9bf09383a6e75424d10aad27e14ec2b62444a5cc742"],"state_sha256":"7a874dd93f107e6f3e52d2bfe73d282a8457554bc2617b5c9b0323efb77de164"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dwQauX4kbI6JGejgOaUx8u4FSqWUQSxmCBMuvpVEMZyroL3/mhgeW2pyQwwB/nVapGKj7hTJfUx8R9ODKB/0Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T09:25:36.420066Z","bundle_sha256":"983e9ddaf9eb6ecdba7be01514e0ada78bfb4d5ce559f3b77c3131d38f89ba64"}}