{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:B6HQ4U2Y4346Z3HFDCQUJSMQBK","short_pith_number":"pith:B6HQ4U2Y","canonical_record":{"source":{"id":"1207.7055","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2012-07-30T19:42:31Z","cross_cats_sorted":[],"title_canon_sha256":"d41b0fd22c8e80e43f8ce938a270e204e00678c71532da75df599da3af561749","abstract_canon_sha256":"7688bf03024c9ab299ace8a00dbd3bff9ea8fdb0d329532db058dd944089437c"},"schema_version":"1.0"},"canonical_sha256":"0f8f0e5358e6f9ecece518a144c9900a9a89f0a641f1c6be4c6a783516769fe8","source":{"kind":"arxiv","id":"1207.7055","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1207.7055","created_at":"2026-05-18T03:49:47Z"},{"alias_kind":"arxiv_version","alias_value":"1207.7055v1","created_at":"2026-05-18T03:49:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1207.7055","created_at":"2026-05-18T03:49:47Z"},{"alias_kind":"pith_short_12","alias_value":"B6HQ4U2Y4346","created_at":"2026-05-18T12:26:58Z"},{"alias_kind":"pith_short_16","alias_value":"B6HQ4U2Y4346Z3HF","created_at":"2026-05-18T12:26:58Z"},{"alias_kind":"pith_short_8","alias_value":"B6HQ4U2Y","created_at":"2026-05-18T12:26:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:B6HQ4U2Y4346Z3HFDCQUJSMQBK","target":"record","payload":{"canonical_record":{"source":{"id":"1207.7055","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2012-07-30T19:42:31Z","cross_cats_sorted":[],"title_canon_sha256":"d41b0fd22c8e80e43f8ce938a270e204e00678c71532da75df599da3af561749","abstract_canon_sha256":"7688bf03024c9ab299ace8a00dbd3bff9ea8fdb0d329532db058dd944089437c"},"schema_version":"1.0"},"canonical_sha256":"0f8f0e5358e6f9ecece518a144c9900a9a89f0a641f1c6be4c6a783516769fe8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:49:47.872548Z","signature_b64":"IJeyhDjnK7RNmqiuOWPOeNhpnH1Sfpm/4euZY5qmAjR8MXBffpdmSFmDPSNUmbdLEqaz+S+BVeuDSdt1ZuJxDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0f8f0e5358e6f9ecece518a144c9900a9a89f0a641f1c6be4c6a783516769fe8","last_reissued_at":"2026-05-18T03:49:47.871879Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:49:47.871879Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1207.7055","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":"2026-05-18T03:49:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vlpoVlrMjnThmDgZ3wo9lO1gPbd6sGGwSdvY5IAvyxbEKHZGMzkgx9vClExzyDaZ3YhITEhujn593OKIHmJNDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T19:25:35.707712Z"},"content_sha256":"dc21d172a9ccad49034e215abeea5d0209ec39a0b82add4e44bca4458d6f5685","schema_version":"1.0","event_id":"sha256:dc21d172a9ccad49034e215abeea5d0209ec39a0b82add4e44bca4458d6f5685"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:B6HQ4U2Y4346Z3HFDCQUJSMQBK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimizing MapReduce for Highly Distributed Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Abhishek Chandra, Benjamin Heintz, Ramesh K. Sitaraman","submitted_at":"2012-07-30T19:42:31Z","abstract_excerpt":"MapReduce, the popular programming paradigm for large-scale data processing, has traditionally been deployed over tightly-coupled clusters where the data is already locally available. The assumption that the data and compute resources are available in a single central location, however, no longer holds for many emerging applications in commercial, scientific and social networking domains, where the data is generated in a geographically distributed manner. Further, the computational resources needed for carrying out the data analysis may be distributed across multiple data centers or community "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1207.7055","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":"2026-05-18T03:49:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"POIokI3DHcyQj2wabfoWdYJdZC78PHEELjFqA4YYk5TOrqKoBHzCecP4tjVmuoXidDwdifmGfARuHFTDmPCVAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T19:25:35.708056Z"},"content_sha256":"9509c60cb90c5ec1398e409dca9327dae5f93b74c51ff26e71c151bc6b77f089","schema_version":"1.0","event_id":"sha256:9509c60cb90c5ec1398e409dca9327dae5f93b74c51ff26e71c151bc6b77f089"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B6HQ4U2Y4346Z3HFDCQUJSMQBK/bundle.json","state_url":"https://pith.science/pith/B6HQ4U2Y4346Z3HFDCQUJSMQBK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B6HQ4U2Y4346Z3HFDCQUJSMQBK/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":"2026-06-21T19:25:35Z","links":{"resolver":"https://pith.science/pith/B6HQ4U2Y4346Z3HFDCQUJSMQBK","bundle":"https://pith.science/pith/B6HQ4U2Y4346Z3HFDCQUJSMQBK/bundle.json","state":"https://pith.science/pith/B6HQ4U2Y4346Z3HFDCQUJSMQBK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B6HQ4U2Y4346Z3HFDCQUJSMQBK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:B6HQ4U2Y4346Z3HFDCQUJSMQBK","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":"7688bf03024c9ab299ace8a00dbd3bff9ea8fdb0d329532db058dd944089437c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2012-07-30T19:42:31Z","title_canon_sha256":"d41b0fd22c8e80e43f8ce938a270e204e00678c71532da75df599da3af561749"},"schema_version":"1.0","source":{"id":"1207.7055","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1207.7055","created_at":"2026-05-18T03:49:47Z"},{"alias_kind":"arxiv_version","alias_value":"1207.7055v1","created_at":"2026-05-18T03:49:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1207.7055","created_at":"2026-05-18T03:49:47Z"},{"alias_kind":"pith_short_12","alias_value":"B6HQ4U2Y4346","created_at":"2026-05-18T12:26:58Z"},{"alias_kind":"pith_short_16","alias_value":"B6HQ4U2Y4346Z3HF","created_at":"2026-05-18T12:26:58Z"},{"alias_kind":"pith_short_8","alias_value":"B6HQ4U2Y","created_at":"2026-05-18T12:26:58Z"}],"graph_snapshots":[{"event_id":"sha256:9509c60cb90c5ec1398e409dca9327dae5f93b74c51ff26e71c151bc6b77f089","target":"graph","created_at":"2026-05-18T03:49:47Z","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":"MapReduce, the popular programming paradigm for large-scale data processing, has traditionally been deployed over tightly-coupled clusters where the data is already locally available. The assumption that the data and compute resources are available in a single central location, however, no longer holds for many emerging applications in commercial, scientific and social networking domains, where the data is generated in a geographically distributed manner. Further, the computational resources needed for carrying out the data analysis may be distributed across multiple data centers or community ","authors_text":"Abhishek Chandra, Benjamin Heintz, Ramesh K. Sitaraman","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2012-07-30T19:42:31Z","title":"Optimizing MapReduce for Highly Distributed Environments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1207.7055","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:dc21d172a9ccad49034e215abeea5d0209ec39a0b82add4e44bca4458d6f5685","target":"record","created_at":"2026-05-18T03:49:47Z","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":"7688bf03024c9ab299ace8a00dbd3bff9ea8fdb0d329532db058dd944089437c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2012-07-30T19:42:31Z","title_canon_sha256":"d41b0fd22c8e80e43f8ce938a270e204e00678c71532da75df599da3af561749"},"schema_version":"1.0","source":{"id":"1207.7055","kind":"arxiv","version":1}},"canonical_sha256":"0f8f0e5358e6f9ecece518a144c9900a9a89f0a641f1c6be4c6a783516769fe8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0f8f0e5358e6f9ecece518a144c9900a9a89f0a641f1c6be4c6a783516769fe8","first_computed_at":"2026-05-18T03:49:47.871879Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:49:47.871879Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IJeyhDjnK7RNmqiuOWPOeNhpnH1Sfpm/4euZY5qmAjR8MXBffpdmSFmDPSNUmbdLEqaz+S+BVeuDSdt1ZuJxDg==","signature_status":"signed_v1","signed_at":"2026-05-18T03:49:47.872548Z","signed_message":"canonical_sha256_bytes"},"source_id":"1207.7055","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dc21d172a9ccad49034e215abeea5d0209ec39a0b82add4e44bca4458d6f5685","sha256:9509c60cb90c5ec1398e409dca9327dae5f93b74c51ff26e71c151bc6b77f089"],"state_sha256":"7f983d47d721250a999130cd77407d0e7f794caf8a04f93f7ae8677fe5c96c9b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R3DwCtsYu4z/I040R+qd3zqaU+l+zyvd1xnL6ZgCJ8YyWEAfthAjPTXOw6l8L3yuZKY5RACuo3Ha7tqFXynRBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-21T19:25:35.709985Z","bundle_sha256":"ae592ad16156e816bb88e13a0d85a1c9f566a2d85c3818651e60ac25259cba81"}}