{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:24DL2GFDEXPL3PKWNX6RBEKRNX","short_pith_number":"pith:24DL2GFD","schema_version":"1.0","canonical_sha256":"d706bd18a325debdbd566dfd1091516df7cad36563bf28496ddbb303dd72f092","source":{"kind":"arxiv","id":"1602.04256","version":2},"attestation_state":"computed","paper":{"title":"Squish: Near-Optimal Compression for Archival of Relational Datasets","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Aditya Parameswaran, Yihan Gao","submitted_at":"2016-02-12T22:46:57Z","abstract_excerpt":"Relational datasets are being generated at an alarmingly rapid rate across organizations and industries. Compressing these datasets could significantly reduce storage and archival costs. Traditional compression algorithms, e.g., gzip, are suboptimal for compressing relational datasets since they ignore the table structure and relationships between attributes.\n  We study compression algorithms that leverage the relational structure to compress datasets to a much greater extent. We develop Squish, a system that uses a combination of Bayesian Networks and Arithmetic Coding to capture multiple kin"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1602.04256","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2016-02-12T22:46:57Z","cross_cats_sorted":[],"title_canon_sha256":"5c0a4eab44e59db92fd7855cce4451dbf5f8f02ecbfd63024da0fffc8c0d1419","abstract_canon_sha256":"51f3b4391ace8af1c5eb17daac5dce5b87b1ce49ede8cef0bc6b93c1690ab9e6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:12:16.788832Z","signature_b64":"sEeykjN4qCY8kUp/xFbt7Iu2GJH4c0FnXk8C7fdSWIBQxCNT9XIh/ajWSyJbuFCSEqjnNS75glds3JnSzPOHAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d706bd18a325debdbd566dfd1091516df7cad36563bf28496ddbb303dd72f092","last_reissued_at":"2026-05-18T01:12:16.788491Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:12:16.788491Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Squish: Near-Optimal Compression for Archival of Relational Datasets","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Aditya Parameswaran, Yihan Gao","submitted_at":"2016-02-12T22:46:57Z","abstract_excerpt":"Relational datasets are being generated at an alarmingly rapid rate across organizations and industries. Compressing these datasets could significantly reduce storage and archival costs. Traditional compression algorithms, e.g., gzip, are suboptimal for compressing relational datasets since they ignore the table structure and relationships between attributes.\n  We study compression algorithms that leverage the relational structure to compress datasets to a much greater extent. We develop Squish, a system that uses a combination of Bayesian Networks and Arithmetic Coding to capture multiple kin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.04256","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1602.04256","created_at":"2026-05-18T01:12:16.788543+00:00"},{"alias_kind":"arxiv_version","alias_value":"1602.04256v2","created_at":"2026-05-18T01:12:16.788543+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.04256","created_at":"2026-05-18T01:12:16.788543+00:00"},{"alias_kind":"pith_short_12","alias_value":"24DL2GFDEXPL","created_at":"2026-05-18T12:29:52.810259+00:00"},{"alias_kind":"pith_short_16","alias_value":"24DL2GFDEXPL3PKW","created_at":"2026-05-18T12:29:52.810259+00:00"},{"alias_kind":"pith_short_8","alias_value":"24DL2GFD","created_at":"2026-05-18T12:29:52.810259+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/24DL2GFDEXPL3PKWNX6RBEKRNX","json":"https://pith.science/pith/24DL2GFDEXPL3PKWNX6RBEKRNX.json","graph_json":"https://pith.science/api/pith-number/24DL2GFDEXPL3PKWNX6RBEKRNX/graph.json","events_json":"https://pith.science/api/pith-number/24DL2GFDEXPL3PKWNX6RBEKRNX/events.json","paper":"https://pith.science/paper/24DL2GFD"},"agent_actions":{"view_html":"https://pith.science/pith/24DL2GFDEXPL3PKWNX6RBEKRNX","download_json":"https://pith.science/pith/24DL2GFDEXPL3PKWNX6RBEKRNX.json","view_paper":"https://pith.science/paper/24DL2GFD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1602.04256&json=true","fetch_graph":"https://pith.science/api/pith-number/24DL2GFDEXPL3PKWNX6RBEKRNX/graph.json","fetch_events":"https://pith.science/api/pith-number/24DL2GFDEXPL3PKWNX6RBEKRNX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/24DL2GFDEXPL3PKWNX6RBEKRNX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/24DL2GFDEXPL3PKWNX6RBEKRNX/action/storage_attestation","attest_author":"https://pith.science/pith/24DL2GFDEXPL3PKWNX6RBEKRNX/action/author_attestation","sign_citation":"https://pith.science/pith/24DL2GFDEXPL3PKWNX6RBEKRNX/action/citation_signature","submit_replication":"https://pith.science/pith/24DL2GFDEXPL3PKWNX6RBEKRNX/action/replication_record"}},"created_at":"2026-05-18T01:12:16.788543+00:00","updated_at":"2026-05-18T01:12:16.788543+00:00"}