{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:GVUSPWDP55SGRPJUQJCUER72KJ","short_pith_number":"pith:GVUSPWDP","canonical_record":{"source":{"id":"1805.08650","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2018-05-22T14:59:02Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"c6d8e16c96916aaf0139a1e56ce4950c8763694cf2f411451ca24d552025182e","abstract_canon_sha256":"68ba8c4f1c52523b6581573ba73421a9fd07cae63b866c32843e0579080207b2"},"schema_version":"1.0"},"canonical_sha256":"356927d86fef6468bd3482454247fa52702bcb9cbcdf51a9e2e223f1fbf3ccd6","source":{"kind":"arxiv","id":"1805.08650","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.08650","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"arxiv_version","alias_value":"1805.08650v1","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.08650","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"pith_short_12","alias_value":"GVUSPWDP55SG","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GVUSPWDP55SGRPJU","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GVUSPWDP","created_at":"2026-05-18T12:32:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:GVUSPWDP55SGRPJUQJCUER72KJ","target":"record","payload":{"canonical_record":{"source":{"id":"1805.08650","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2018-05-22T14:59:02Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"c6d8e16c96916aaf0139a1e56ce4950c8763694cf2f411451ca24d552025182e","abstract_canon_sha256":"68ba8c4f1c52523b6581573ba73421a9fd07cae63b866c32843e0579080207b2"},"schema_version":"1.0"},"canonical_sha256":"356927d86fef6468bd3482454247fa52702bcb9cbcdf51a9e2e223f1fbf3ccd6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:15:25.555658Z","signature_b64":"6orS76b1oEZoLSdb6fLQU7xyw4wZBT8I8r5lB0osLu/OYmqdS3H46CfQx1o1IrFHhX/UuTBtlBTGC96sVlN5Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"356927d86fef6468bd3482454247fa52702bcb9cbcdf51a9e2e223f1fbf3ccd6","last_reissued_at":"2026-05-18T00:15:25.554923Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:15:25.554923Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.08650","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":"2026-05-18T00:15:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cXL8SehBjxh/nVUwO4+GRIYrQ5ry94BeHy4fGWdfSCOWPCDey5kat45o9CBirgefwJlpXTunfXNj5ZJCE92ZBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T00:59:39.964161Z"},"content_sha256":"beedc3944ef3ae89b8a3cc67819708533244ae287de160361773e079df94bbba","schema_version":"1.0","event_id":"sha256:beedc3944ef3ae89b8a3cc67819708533244ae287de160361773e079df94bbba"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:GVUSPWDP55SGRPJUQJCUER72KJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Cache-based Multi-query Optimization for Data-intensive Scalable Computing Frameworks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.DB","authors_text":"Damiano Carra, Pietro Michiardi, Sara Migliorini","submitted_at":"2018-05-22T14:59:02Z","abstract_excerpt":"In modern large-scale distributed systems, analytics jobs submitted by various users often share similar work, for example scanning and processing the same subset of data. Instead of optimizing jobs independently, which may result in redundant and wasteful processing, multi-query optimization techniques can be employed to save a considerable amount of cluster resources. In this work, we introduce a novel method combining in-memory cache primitives and multi-query optimization, to improve the efficiency of data-intensive, scalable computing frameworks. By careful selection and exploitation of c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.08650","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":""},"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":"2026-05-18T00:15:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qrl8ZrqKiNctagIu/FX2Drs/OYz3ZEL17DqQezfHraMga+vvvyqBRSYp3taGtV3o+OtL6BElkQELk6myvI2wDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T00:59:39.964575Z"},"content_sha256":"f34f18af118d4f756d7f60a740cfde5cb4f688b135553015f3bb5dbbedf350e4","schema_version":"1.0","event_id":"sha256:f34f18af118d4f756d7f60a740cfde5cb4f688b135553015f3bb5dbbedf350e4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GVUSPWDP55SGRPJUQJCUER72KJ/bundle.json","state_url":"https://pith.science/pith/GVUSPWDP55SGRPJUQJCUER72KJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GVUSPWDP55SGRPJUQJCUER72KJ/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":"2026-06-10T00:59:39Z","links":{"resolver":"https://pith.science/pith/GVUSPWDP55SGRPJUQJCUER72KJ","bundle":"https://pith.science/pith/GVUSPWDP55SGRPJUQJCUER72KJ/bundle.json","state":"https://pith.science/pith/GVUSPWDP55SGRPJUQJCUER72KJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GVUSPWDP55SGRPJUQJCUER72KJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:GVUSPWDP55SGRPJUQJCUER72KJ","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":"68ba8c4f1c52523b6581573ba73421a9fd07cae63b866c32843e0579080207b2","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2018-05-22T14:59:02Z","title_canon_sha256":"c6d8e16c96916aaf0139a1e56ce4950c8763694cf2f411451ca24d552025182e"},"schema_version":"1.0","source":{"id":"1805.08650","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.08650","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"arxiv_version","alias_value":"1805.08650v1","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.08650","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"pith_short_12","alias_value":"GVUSPWDP55SG","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GVUSPWDP55SGRPJU","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GVUSPWDP","created_at":"2026-05-18T12:32:25Z"}],"graph_snapshots":[{"event_id":"sha256:f34f18af118d4f756d7f60a740cfde5cb4f688b135553015f3bb5dbbedf350e4","target":"graph","created_at":"2026-05-18T00:15:25Z","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":"In modern large-scale distributed systems, analytics jobs submitted by various users often share similar work, for example scanning and processing the same subset of data. Instead of optimizing jobs independently, which may result in redundant and wasteful processing, multi-query optimization techniques can be employed to save a considerable amount of cluster resources. In this work, we introduce a novel method combining in-memory cache primitives and multi-query optimization, to improve the efficiency of data-intensive, scalable computing frameworks. By careful selection and exploitation of c","authors_text":"Damiano Carra, Pietro Michiardi, Sara Migliorini","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2018-05-22T14:59:02Z","title":"Cache-based Multi-query Optimization for Data-intensive Scalable Computing Frameworks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.08650","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:beedc3944ef3ae89b8a3cc67819708533244ae287de160361773e079df94bbba","target":"record","created_at":"2026-05-18T00:15:25Z","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":"68ba8c4f1c52523b6581573ba73421a9fd07cae63b866c32843e0579080207b2","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2018-05-22T14:59:02Z","title_canon_sha256":"c6d8e16c96916aaf0139a1e56ce4950c8763694cf2f411451ca24d552025182e"},"schema_version":"1.0","source":{"id":"1805.08650","kind":"arxiv","version":1}},"canonical_sha256":"356927d86fef6468bd3482454247fa52702bcb9cbcdf51a9e2e223f1fbf3ccd6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"356927d86fef6468bd3482454247fa52702bcb9cbcdf51a9e2e223f1fbf3ccd6","first_computed_at":"2026-05-18T00:15:25.554923Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:15:25.554923Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6orS76b1oEZoLSdb6fLQU7xyw4wZBT8I8r5lB0osLu/OYmqdS3H46CfQx1o1IrFHhX/UuTBtlBTGC96sVlN5Bw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:15:25.555658Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.08650","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:beedc3944ef3ae89b8a3cc67819708533244ae287de160361773e079df94bbba","sha256:f34f18af118d4f756d7f60a740cfde5cb4f688b135553015f3bb5dbbedf350e4"],"state_sha256":"0dc4975ab0b83d32aff69d3751969c76f84737130b7e6701ec87619fb94e098d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ygQXqwAGgdtkONPxDF1KdnFOPVP8cQN8tovvIZ3TesOAaf7LDRcB5WDzFsb0aJQ87G39X2Zy55xaerOVOJOTAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T00:59:39.967089Z","bundle_sha256":"f42907f9e1e6f10f5f5f8a1de8511851e515c24c3621c2a8a3b7d732f0cd2820"}}