{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:EDYMHLGLTNMHIMYD2N6BFREKZB","short_pith_number":"pith:EDYMHLGL","schema_version":"1.0","canonical_sha256":"20f0c3accb9b58743303d37c12c48ac8566a2808251f707009b03dcb923dae1d","source":{"kind":"arxiv","id":"1208.4174","version":1},"attestation_state":"computed","paper":{"title":"Interactive Analytical Processing in Big Data Systems: A Cross-Industry Study of MapReduce Workloads","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Randy Katz, Sara Alspaugh, Yanpei Chen","submitted_at":"2012-08-21T02:53:55Z","abstract_excerpt":"Within the past few years, organizations in diverse industries have adopted MapReduce-based systems for large-scale data processing. Along with these new users, important new workloads have emerged which feature many small, short, and increasingly interactive jobs in addition to the large, long-running batch jobs for which MapReduce was originally designed. As interactive, large-scale query processing is a strength of the RDBMS community, it is important that lessons from that field be carried over and applied where possible in this new domain. However, these new workloads have not yet been de"},"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":"1208.4174","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2012-08-21T02:53:55Z","cross_cats_sorted":[],"title_canon_sha256":"55dd743a5936824942be87b8a73bb2e78b59f39cc1bba1e167ca9ba7caec93e6","abstract_canon_sha256":"a49da45ae7425f83a20bd7f21f905930090d8b101780e42764aa8a9e107f0890"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:48:24.782945Z","signature_b64":"pdaMWmwpkbrB+I62Z+snKfHcYfIW2dJUDlVKOVlMCQ5SrDfzlyycMGkWR8SO6/RdRg9hYpHbUGJWwHK3dYGyAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"20f0c3accb9b58743303d37c12c48ac8566a2808251f707009b03dcb923dae1d","last_reissued_at":"2026-05-18T03:48:24.782168Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:48:24.782168Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Interactive Analytical Processing in Big Data Systems: A Cross-Industry Study of MapReduce Workloads","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Randy Katz, Sara Alspaugh, Yanpei Chen","submitted_at":"2012-08-21T02:53:55Z","abstract_excerpt":"Within the past few years, organizations in diverse industries have adopted MapReduce-based systems for large-scale data processing. Along with these new users, important new workloads have emerged which feature many small, short, and increasingly interactive jobs in addition to the large, long-running batch jobs for which MapReduce was originally designed. As interactive, large-scale query processing is a strength of the RDBMS community, it is important that lessons from that field be carried over and applied where possible in this new domain. However, these new workloads have not yet been de"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1208.4174","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1208.4174","created_at":"2026-05-18T03:48:24.782290+00:00"},{"alias_kind":"arxiv_version","alias_value":"1208.4174v1","created_at":"2026-05-18T03:48:24.782290+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1208.4174","created_at":"2026-05-18T03:48:24.782290+00:00"},{"alias_kind":"pith_short_12","alias_value":"EDYMHLGLTNMH","created_at":"2026-05-18T12:27:04.183437+00:00"},{"alias_kind":"pith_short_16","alias_value":"EDYMHLGLTNMHIMYD","created_at":"2026-05-18T12:27:04.183437+00:00"},{"alias_kind":"pith_short_8","alias_value":"EDYMHLGL","created_at":"2026-05-18T12:27:04.183437+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/EDYMHLGLTNMHIMYD2N6BFREKZB","json":"https://pith.science/pith/EDYMHLGLTNMHIMYD2N6BFREKZB.json","graph_json":"https://pith.science/api/pith-number/EDYMHLGLTNMHIMYD2N6BFREKZB/graph.json","events_json":"https://pith.science/api/pith-number/EDYMHLGLTNMHIMYD2N6BFREKZB/events.json","paper":"https://pith.science/paper/EDYMHLGL"},"agent_actions":{"view_html":"https://pith.science/pith/EDYMHLGLTNMHIMYD2N6BFREKZB","download_json":"https://pith.science/pith/EDYMHLGLTNMHIMYD2N6BFREKZB.json","view_paper":"https://pith.science/paper/EDYMHLGL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1208.4174&json=true","fetch_graph":"https://pith.science/api/pith-number/EDYMHLGLTNMHIMYD2N6BFREKZB/graph.json","fetch_events":"https://pith.science/api/pith-number/EDYMHLGLTNMHIMYD2N6BFREKZB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EDYMHLGLTNMHIMYD2N6BFREKZB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EDYMHLGLTNMHIMYD2N6BFREKZB/action/storage_attestation","attest_author":"https://pith.science/pith/EDYMHLGLTNMHIMYD2N6BFREKZB/action/author_attestation","sign_citation":"https://pith.science/pith/EDYMHLGLTNMHIMYD2N6BFREKZB/action/citation_signature","submit_replication":"https://pith.science/pith/EDYMHLGLTNMHIMYD2N6BFREKZB/action/replication_record"}},"created_at":"2026-05-18T03:48:24.782290+00:00","updated_at":"2026-05-18T03:48:24.782290+00:00"}