docs/towards_dist_search/Distributed_search.md
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- This local index is put on an (IPFS) cluster.
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- Tokenise the query (split into words)
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- Number of downloaded bytes per second versus the number of peers
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- Bring the downed node back online. The data that belongs on this node (hopefully) begins to flow back into the node.
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- [IPFS Cluster Documentation](https://cluster.ipfs.io/documentation/ "https://cluster.ipfs.io/documentation/")
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- Sanitize the query (stemming all the words, making all letters lowercase, removing punctuation)
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return [filename for filename in invertedIndex[word].keys()]
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listOfLists.append(one_word_query(word))
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setted = set(listOfLists[0]).intersection(*listOfLists)
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for filename in setted:
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- Node failure
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- No local discovery.
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- [Tika Supported Document Formats](https://tika.apache.org/1.4/formats.html "https://tika.apache.org/1.4/formats.html")
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- IPFS does not guarantee redundancy. We can use IPFS clustering.
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string = pattern.sub(' ',string)
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for word in string.split():
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temp = []
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- Number of hashes crawled per second per-peer versus the number of peers
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walk through the directory structure to fetch each file_path and
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if word in invertedIndex.keys():
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string = pattern.sub(' ',string)
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- After a while, pull the data from the agent to check that data that was sent to its neighbours when it was down is stored correctly.
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### [Source](https://niverel.tymyrddin.space/en/play/stones/upsidedown/testing)
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- Provider nodes that wish to participate, parse and index only the files they have added to a dweb (DHT hashes) and that have world file permissions.
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pattern = re.compile('[\W_]+')
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- Scalability indicators
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- Take an agent offline (check that it has gone down and is inaccessible) and verify that all the data appears to be working.
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for i in range(len(temp)):
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### [Source](https://niverel.tymyrddin.space/en/play/stones/upsidedown/testing)
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return []
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result = []
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- Performance indicators
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result += one_word_query(word)
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for ind in range(len(temp[i])):
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for word in string.split():
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if set(temp[0]).intersection(*temp):
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- If automated, this may require adding data entry points in the API that are only used for testing.
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- Only popular indexes will be able to get a decent speed.
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pattern = re.compile('[\W_]+')
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return list(set(result))
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for word in string.split():
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- We can run a few web agent type ipfs nodes in a cluster that pin all the indexes. Give these enough bandwidth and we have some basis nodes that can act as mirrors and can also be served via HTTPS (the internet-facing demo version).
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result.append(filename)
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- No transports other than, for example, via Tor (an overlay network consisting of more than seven thousand relays to conceal a user's location and usage from anyone conducting network surveillance or traffic analysis).
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else:
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temp.append(invertedIndex[word][filename][:])
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- Number of hashes crawled per second versus different CPU loads/platforms
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- Predictive analysis
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return rankResults(result, string)
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temp[i][ind] -= i
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- [Yggdrasil Version 0.3.6](https://yggdrasil-network.github.io/2019/08/03/release-v0-3-6.html "https://yggdrasil-network.github.io/2019/08/03/release-v0-3-6.html"), august 2019, first version with API
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- Throughput of a peer versus the number of crawled job queues (to determine the optimal number of crawl job queues) per platform (differentiate using agent attributes).
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word = pattern.sub(' ',word)
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pattern = re.compile('[\W_]+')
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listOfLists, result = [],[]
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