import heapq import json import logging import os import re from collections import defaultdict, Counter from datetime import date from enum import Enum from urllib.parse import urlparse import mrjob.util import tldextract import ujson from hyperloglog import HyperLogLog from isoweek import Week from mrjob.job import MRJob, MRStep from mrjob.protocol import JSONProtocol, RawValueProtocol HYPERLOGLOG_ERROR = .01 # threshold when to add a HyperLogLog for SURT domains MIN_SURT_HLL_SIZE = 50000 LOGGING_FORMAT = '%(asctime)s: [%(levelname)s]: %(message)s' LOGGING_LEVEL = logging.INFO LOG = logging.getLogger('CCStatsJob') mrjob.util.log_to_stream(format=LOGGING_FORMAT, level=LOGGING_LEVEL, name='CCStatsJob') class MonthlyCrawl: """Enumeration of monthly crawl archives""" by_name = { 'CC-MAIN-2008-2009': 88, 'CC-MAIN-2009-2010': 89, 'CC-MAIN-2012': 90, 'CC-MAIN-2013-20': 91, 'CC-MAIN-2013-48': 92, 'CC-MAIN-2014-10': 93, 'CC-MAIN-2014-15': 94, 'CC-MAIN-2014-23': 95, 'CC-MAIN-2014-35': 96, 'CC-MAIN-2014-41': 97, 'CC-MAIN-2014-42': 98, 'CC-MAIN-2014-49': 99, 'CC-MAIN-2014-52': 0, 'CC-MAIN-2015-06': 1, 'CC-MAIN-2015-11': 2, 'CC-MAIN-2015-14': 3, 'CC-MAIN-2015-18': 4, 'CC-MAIN-2015-22': 5, 'CC-MAIN-2015-27': 6, 'CC-MAIN-2015-32': 7, 'CC-MAIN-2015-35': 8, 'CC-MAIN-2015-40': 9, 'CC-MAIN-2015-48': 10, 'CC-MAIN-2016-07': 11, 'CC-MAIN-2016-18': 12, 'CC-MAIN-2016-22': 13, 'CC-MAIN-2016-26': 14, 'CC-MAIN-2016-30': 15, 'CC-MAIN-2016-36': 16, 'CC-MAIN-2016-40': 17, 'CC-MAIN-2016-44': 18, 'CC-MAIN-2016-50': 19, 'CC-MAIN-2017-04': 20, 'CC-MAIN-2017-09': 21, 'CC-MAIN-2017-13': 22, 'CC-MAIN-2017-17': 23, 'CC-MAIN-2017-22': 24, 'CC-MAIN-2017-26': 25, 'CC-MAIN-2017-30': 26, 'CC-MAIN-2017-34': 27, 'CC-MAIN-2017-39': 28, 'CC-MAIN-2017-43': 29, 'CC-MAIN-2017-47': 30, 'CC-MAIN-2017-51': 31, 'CC-MAIN-2018-05': 32, 'CC-MAIN-2018-09': 33, 'CC-MAIN-2018-13': 34, 'CC-MAIN-2018-17': 35, 'CC-MAIN-2018-22': 36, 'CC-MAIN-2018-26': 37, 'CC-MAIN-2018-30': 38, 'CC-MAIN-2018-34': 39, 'CC-MAIN-2018-39': 40, 'CC-MAIN-2018-43': 41, 'CC-MAIN-2018-47': 42, 'CC-MAIN-2018-51': 43, 'CC-MAIN-2019-04': 44, 'CC-MAIN-2019-09': 45, 'CC-MAIN-2019-13': 46, 'CC-MAIN-2019-18': 47, 'CC-MAIN-2019-22': 48, 'CC-MAIN-2019-26': 49, 'CC-MAIN-2019-30': 50, 'CC-MAIN-2019-35': 51, 'CC-MAIN-2019-39': 52, 'CC-MAIN-2019-43': 53, 'CC-MAIN-2019-47': 54, 'CC-MAIN-2019-51': 55, 'CC-MAIN-2020-05': 56, 'CC-MAIN-2020-10': 57, 'CC-MAIN-2020-16': 58, 'CC-MAIN-2020-24': 59, } by_id = dict(map(reversed, by_name.items())) @staticmethod def get_by_name(name): return MonthlyCrawl.by_name[name] @staticmethod def to_name(crawl): return MonthlyCrawl.by_id[crawl] @staticmethod def to_bit_mask(crawl): return (1 << crawl) @staticmethod def date_of(crawl): if crawl == 'CC-MAIN-2008-2009': return date(2009, 1, 12) if crawl == 'CC-MAIN-2009-2010': return date(2010, 9, 25) if crawl == 'CC-MAIN-2012': return date(2012, 11, 2) [_, _, year, week] = crawl.split('-') return Week(int(year), int(week)).monday() @staticmethod def short_name(name): return name.replace('CC-MAIN-', '') @staticmethod def get_last(n): return sorted(MonthlyCrawl.by_name.keys())[-n:] class MonthlyCrawlSet: """Dense representation of a list of monthly crawls. Represent in which crawls a given item (URL, but also domain, host, digest) occurs. """ def __init__(self, crawls=0): self.bits = crawls def add(self, crawl): self.bits |= MonthlyCrawl.to_bit_mask(crawl) def update(self, *others): for other in others: self.bits |= other.get_bits() def clear(self): self.bits = 0 def discard(self, crawl): self.bits &= ~MonthlyCrawl.to_bit_mask(crawl) def __contains__(self, crawl): return (self.bits & MonthlyCrawl.to_bit_mask(crawl)) != 0 def __len__(self): i = self.bits i = i - ((i >> 1) & 0x55555555) i = (i & 0x33333333) + ((i >> 2) & 0x33333333) return (((i + (i >> 4) & 0xF0F0F0F) * 0x1010101) & 0xffffffff) >> 24 def get_bits(self): return self.bits def get_crawls(self): i = self.bits r = 0 while (i): if (i & 1): yield r r += 1 i >>= 1 def is_new(self, crawl): """True if there are no older crawls in set (no lower id)""" if (self.bits == 0): return True i = self.bits i = (i ^ (i - 1)) >> 1 # set trailing 0s to 1s and zero rest r = 0 while (i): if r == crawl: return True r += 1 i >>= 1 if (r < crawl): return False return True def is_newest(self, crawl): """True if crawl is the newest crawl in set (highest id)""" # i = self.bits # j = MonthlyCrawl.to_bit_mask(crawl) # return (i & ~j) < j return self.bits.bit_length() == (crawl + 1) class CST(Enum): """Enum for crawl statistics types. Every line (key-value pair) has a marker which indicates the type of the count / frequency: - pages, URLs, hosts, etc. - size (number of unique items), histograms, etc. The type marker (the first element in the key tuple) determines the format of the line (key-value pair): <<type, key_params...>, <values...>> The format may vary for different steps (job, mapper, reducer). The count job (CCCountJob) uses the numeric types to reduce the data size, while CCCountJob outputs the type names for better readability. Types of countable items # <<type, item, crawl>, <count(s)>> # For hosts, domains, etc. MultiCount is used to hold two counts - # the number of pages and URLs per item.""" url = 0 """(unique) URL""" digest = 1 """(unique) content digest (MD5)""" host = 2 """hostname ("www.commoncrawl.org")""" domain = 3 """pay-level domain or private domain ("commoncrawl.org")""" tld = 4 """public suffix ("org" or "co.uk") - not necessarily a TLD / "top-level domain" according to https://github.com/google/guava/wiki/InternetDomainNameExplained - here following https://github.com/john-kurkowski/tldextract""" surt_domain = 5 """surt_domain :- SURT domain ("org,commoncrawl") - Sort-friendly URI Reordering Transform, cf. http://crawler.archive.org/articles/user_manual/glossary.html#surt""" scheme = 6 """URI scheme ("http", "https") see https://en.wikipedia.org/wiki/Uniform_Resource_Identifier#Syntax""" mimetype = 7 """MIME type / media type / content type - as sent by the server as "Content-Type" in the HTTP header, weakly normalized, not verified""" mimetype_detected = 77 """MIME type detected based on content, URL and HTTP Content-Type""" page = 8 """number of successfully fetched pages (HTTP status 200), including URL-level and content-level duplicates""" fetch = 9 """number of fetches, including 404s, redirects, robots.txt, etc. - since CC-MAIN-2016-50""" http_status = 10 """detected charset - since CC-MAIN-2018-34""" charset = 11 """detected languages or combination of languages - since CC-MAIN-2018-34 NOTE: since gld2 identifies 160 languages and up to 3 languages, the number of possible combinations is too high (4 millions) and only the more common ones are preserved""" languages = 12 """primary language of the document (first of the detected languages) - since CC-MAIN-2018-34""" primary_language = 13 """number of HTTP status codes (200, 404, etc.) - since CC-MAIN-2016-50""" crawl_status = 55 """crawl status (successful fetches, 404s, exceptions, etc.) - following Nutch CrawlDatum status codes - similar to HTTP status but less fine-grained - includes crawler-specific statuses (e.g., "denied by robots.txt")""" robotstxt_status = 56 """HTTP status of robots.txt responses""" size = 90 """size of a crawl (number of unique items): - pages, - URLs (one URL may be fetched multiple times), - content digests, - domains, hosts, top-level domains - mime types - etc. format: <<size, item_type, crawl>, number_of_unique_items>""" size_estimate = 91 """estimates for unique URLs and content digests - estimates by HyperLogLog probabilistic counters""" size_estimate_for = 92 """estimates per large-sized item (domains, hosts, TLDs, SURT domains) - aimed to estimate domain coverage over time / multiple crawls - CC-MAIN-2016-44 adds HyperLogLogs for SURT domain (>=50,000 URLs) format: <<size_estimate_for, per_item_type, per_item, item_type, crawl>, hll>""" size_robotstxt = 93 """number of robots.txt fetches""" new_items = 95 """new items (URLs, content digests) for a given crawl - first seen in this crawl, not observed in previous crawls - only with exact counts for all crawls - could be estimated by HyperLogLog set operations otherwise""" histogram = 96 """frequency of item counts per page or URL format: <<type, item_type, crawl, counted_per, count>, frequency>""" class MultiCount(defaultdict): """Dictionary with multiple counters for the same key""" def __init__(self, size): self.default_factory = lambda: [0]*size self.size = size def incr(self, key, *counts): for i in range(0, self.size): self[key][i] += counts[i] @staticmethod def compress(size, counts): compress_from = size-1 last_val = counts[compress_from] while compress_from > 0 and last_val == counts[compress_from-1]: compress_from -= 1 if compress_from == 0: return counts[0] else: return counts[0:compress_from+1] def get_compressed(self, key): return MultiCount.compress(self.size, self.get(key)) @staticmethod def get_count(index, value): if isinstance(value, int): return value if len(value) <= index: return value[-1] return value[index] @staticmethod def sum_values(values, compress=True): counts = [0] size = 1 for val in values: if isinstance(val, int): # compressed count, one unique count for i in range(0, size): counts[i] += val else: if len(val) >= size: # enlarge counts array base_count = counts[-1] for j in range(size, len(val)): counts.append(base_count) size = len(val) for i in range(0, len(val)): counts[i] += val[i] if len(val) < size: for j in range(i+1, size): # add compressed counts counts[j] += val[i] if compress: return MultiCount.compress(size, counts) else: return counts class CrawlStatsJSONEncoder(json.JSONEncoder): def default(self, o): if isinstance(o, MonthlyCrawlSet): return o.get_bits() if isinstance(o, HyperLogLog): return CrawlStatsJSONEncoder.json_encode_hyperloglog(o) return json.JSONEncoder.default(self, o) @staticmethod def json_encode_hyperloglog(o): return {'__type__': 'HyperLogLog', 'card': o.card(), 'p': o.p, 'M': o.M, 'm': o.m, 'alpha': o.alpha} class CrawlStatsJSONDecoder(json.JSONDecoder): def __init__(self, *args, **kargs): json.JSONDecoder.__init__(self, object_hook=self.dict_to_object, *args, **kargs) def dict_to_object(self, dic): if '__type__' not in dic: return dic if dic['__type__'] == 'HyperLogLog': try: return CrawlStatsJSONDecoder.json_decode_hyperloglog(dic) except Exception as e: LOG.error('Cannot decode object of type {0}'.format( dic['__type__'])) raise e return dic @staticmethod def json_decode_hyperloglog(dic): hll = HyperLogLog(HYPERLOGLOG_ERROR) hll.p = dic['p'] hll.m = dic['m'] hll.alpha = dic['alpha'] hll.M = dic['M'] return hll class HostDomainCount: """Counts requiring URL parsing (host, domain, TLD, scheme). For each item both total pages and unique URLs are counted. """ IPpattern = re.compile('^\d{1,3}.\d{1,3}.\d{1,3}.\d{1,3}$') def __init__(self): self.hosts = MultiCount(2) self.schemes = MultiCount(2) def add(self, url, count): uri = urlparse(url) host = uri.hostname if host is not None: host = host.lower().strip('.') self.hosts.incr(host, count, 1) self.schemes.incr(uri.scheme, count, 1) def output(self, crawl): domains = MultiCount(3) # pages, URLs, hosts tlds = MultiCount(4) # pages, URLs, hosts, domains for scheme, counts in self.schemes.items(): yield (CST.scheme.value, scheme, crawl), counts for host, counts in self.hosts.items(): yield (CST.host.value, host, crawl), counts try: parsedhost = tldextract.extract(host) hosttld = parsedhost.suffix except TypeError as e: LOG.error('Failed to parse host {}: {}'.format(host, e)) hosttld = None if hosttld is None: hostdomain = '(invalid)' elif hosttld == '': hostdomain = parsedhost.domain if self.IPpattern.match(host): hosttld = '(ip address)' else: hostdomain = '.'.join([parsedhost.domain, parsedhost.suffix]) domains.incr((hostdomain, hosttld), counts[0], counts[1], 1) for dom, counts in domains.items(): tlds.incr(dom[1], counts[0], counts[1], counts[2], 1) yield (CST.domain.value, dom[0], crawl), counts for tld, counts in tlds.items(): yield (CST.tld.value, tld, crawl), counts class SurtDomainCount: """Counters for one single SURT prefix/domain.""" robots_txt_warc_pattern = re.compile('/robotstxt/') def __init__(self, surt_domain): self.surt_domain = surt_domain self.pages = 0 self.url = defaultdict(int) self.digest = defaultdict(lambda: [0, 0]) self.mime = defaultdict(lambda: [0, 0]) self.mime_detected = defaultdict(lambda: [0, 0]) self.charset = defaultdict(lambda: [0, 0]) self.languages = defaultdict(lambda: [0, 0]) self.http_status = defaultdict(int) self.robotstxt_status = defaultdict(lambda: [0, 0]) self.robotstxt_url = defaultdict(int) def add(self, _path, metadata): status = -1 if 'status' in metadata: status = int(metadata['status']) if self.robots_txt_warc_pattern.search(metadata['filename']): self.robotstxt_status[status][0] += 1 if metadata['url'] not in self.robotstxt_url: self.robotstxt_status[status][1] += 1 self.robotstxt_url[metadata['url']] += 1 # do not count robots.txt responses as "ordinary" pages return self.http_status[status] += 1 if status != 200: # skip content-related metrics for non-200 responses return self.pages += 1 mime = 'unk' if 'mime' in metadata: mime = metadata['mime'] self.mime[mime][0] += 1 mime_detected = None if 'mime-detected' in metadata: mime_detected = metadata['mime-detected'] self.mime_detected[mime_detected][0] += 1 charset = None if 'charset' in metadata: charset = metadata['charset'] self.charset[charset][0] += 1 languages = None if 'languages' in metadata: languages = metadata['languages'] self.languages[languages][0] += 1 digest = None if 'digest' in metadata: digest = metadata['digest'] self.digest[digest][0] += 1 if metadata['url'] not in self.url: if digest: self.digest[digest][1] += 1 self.mime[mime][1] += 1 if mime_detected: self.mime_detected[mime_detected][1] += 1 if languages: self.languages[languages][1] += 1 if charset: self.charset[charset][1] += 1 self.url[metadata['url']] += 1 def unique_urls(self): return len(self.url) def output(self, crawl, exact_count=True, min_surt_hll_size=50000): counts = (self.pages, self.unique_urls()) host_domain_count = HostDomainCount() surt_hll = None if self.unique_urls() >= min_surt_hll_size: surt_hll = HyperLogLog(HYPERLOGLOG_ERROR) for url, count in self.url.items(): host_domain_count.add(url, count) if exact_count: yield (CST.url.value, self.surt_domain, url), (crawl, count) if surt_hll is not None: surt_hll.add(url) if exact_count: for digest, counts in self.digest.items(): yield (CST.digest.value, digest), (crawl, counts) for mime, counts in self.mime.items(): yield (CST.mimetype.value, mime, crawl), counts for mime, counts in self.mime_detected.items(): yield (CST.mimetype_detected.value, mime, crawl), counts for charset, counts in self.charset.items(): yield (CST.charset.value, charset, crawl), counts for languages, counts in self.languages.items(): yield (CST.languages.value, languages, crawl), counts # yield primary language prim_l = languages.split(',')[0] yield (CST.primary_language.value, prim_l, crawl), counts for key, val in host_domain_count.output(crawl): yield key, val yield((CST.surt_domain.value, self.surt_domain, crawl), (self.pages, self.unique_urls(), len(host_domain_count.hosts))) if surt_hll is not None: yield((CST.size_estimate_for.value, CST.surt_domain.value, self.surt_domain, CST.url.value, crawl), (self.unique_urls(), CrawlStatsJSONEncoder.json_encode_hyperloglog(surt_hll))) for status, counts in self.http_status.items(): yield (CST.http_status.value, status, crawl), counts for url, count in self.robotstxt_url.items(): yield (CST.size_robotstxt.value, CST.url.value, crawl), 1 yield (CST.size_robotstxt.value, CST.page.value, crawl), count for status, counts in self.robotstxt_status.items(): yield (CST.robotstxt_status.value, status, crawl), counts class UnhandledTypeError(Exception): def __init__(self, outputType): self.message = 'Unhandled type {}\n'.format(outputType) class InputError(Exception): def __init__(self, message): self.message = message class CCStatsJob(MRJob): '''Job to get crawl statistics from Common Crawl index --job=count run count job (first step) to get counts from Common Crawl index files (cdx-*.gz) --job=stats run statistics job (second step) on output from count job''' OUTPUT_PROTOCOL = JSONProtocol JOBCONF = { 'mapreduce.task.timeout': '9600000', 'mapreduce.map.speculative': 'false', 'mapreduce.reduce.speculative': 'false', 'mapreduce.job.jvm.numtasks': '-1', } s3pattern = re.compile('^s3://([^/]+)/(.+)') gzpattern = re.compile('\.gz$') crawlpattern = re.compile('(CC-MAIN-2\d{3}-\d{2})') def configure_args(self): """Custom command line options for common crawl index statistics""" super(CCStatsJob, self).configure_args() self.add_passthru_arg( '--job', dest='job_to_run', default='', choices=['count', 'stats', ''], help='''Job(s) to run ("count", "stats", or empty to run both)''') self.add_passthru_arg( '--exact-counts', dest='exact_counts', action='store_true', default=None, help='''Exact counts for URLs and content digests, this increases the output size significantly''') self.add_passthru_arg( '--no-exact-counts', dest='exact_counts', action='store_false', default=None, help='''No exact counts for URLs and content digests to save storage space and computation time''') self.add_passthru_arg( '--max-top-hosts-domains', dest='max_hosts', type=int, default=200, help='''Max. number of most frequent hosts or domains shown in final statistics (cf. --min-urls-top-host-domain)''') self.add_passthru_arg( '--min-urls-top-host-domain', dest='min_domain_frequency', type=int, default=1, help='''Min. number of URLs required per host or domain shown in final statistics (cf. --max-top-hosts-domains).''') self.add_passthru_arg( '--min-lang-comb-freq', dest='min_lang_comb_freq', type=int, default=1, help='''Min. number of pages required for a combination of detected languages to be shown in final statistics.''') self.add_passthru_arg( '--crawl', dest='crawl', default=None, help='''ID/name of the crawl analyzed (if not given detected from input path)''') def input_protocol(self): if self.options.job_to_run != 'stats': LOG.debug('Reading text input from cdx files') return RawValueProtocol() LOG.debug('Reading JSON input from count job') return JSONProtocol() def hadoop_input_format(self): input_format = self.HADOOP_INPUT_FORMAT if self.options.job_to_run != 'stats': input_format = 'org.apache.hadoop.mapred.TextInputFormat' LOG.info("Setting input format for {} job: {}".format( self.options.job_to_run, input_format)) return input_format def count_mapper_init(self): """Because cdx.gz files cannot be split and mapreduce.input.fileinputformat.split.minsize is set to a value larger than any cdx.gz file, the mapper is guaranteed to process the content of a single cdx file. Input lines of a cdx file are sorted by SURT URL which allows to aggregate URL counts for one SURT domain in memory. It may happen that one SURT domain spans over multiple cdx files. In this case (and without --exact-counts) the count of unique URLs and the URL histograms may be slightly off in case the same URL occurs also in a second cdx file. However, this problem is negligible because there are only 300 cdx files.""" self.counters = Counter() self.cdx_path = os.environ['mapreduce_map_input_file'] LOG.info('Reading {0}'.format(self.cdx_path)) self.crawl_name = None self.crawl = None if self.options.crawl is not None: self.crawl_name = self.options.crawl else: crawl_name_match = self.crawlpattern.search(self.cdx_path) if crawl_name_match is not None: self.crawl_name = crawl_name_match.group(1) else: raise InputError( "Cannot determine ID of monthly crawl from input path {}" .format(self.cdx_path)) if self.crawl_name is None: raise InputError("Name of crawl not given") self.crawl = MonthlyCrawl.get_by_name(self.crawl_name) self.fetches_total = 0 self.pages_total = 0 self.urls_total = 0 self.urls_hll = HyperLogLog(HYPERLOGLOG_ERROR) self.digest_hll = HyperLogLog(HYPERLOGLOG_ERROR) self.url_histogram = Counter() self.count = None # first and last SURT may continue in previous/next cdx self.min_surt_hll_size = 1 self.increment_counter('cdx-stats', 'cdx files processed', 1) def count_mapper(self, _, line): self.fetches_total += 1 if (self.fetches_total % 1000) == 0: self.increment_counter('cdx-stats', 'cdx lines read', 1000) if (self.fetches_total % 100000) == 0: LOG.info('Read {0} cdx lines'.format(self.fetches_total)) else: LOG.debug('Read {0} cdx lines'.format(self.fetches_total)) parts = line.split(' ') [surt_domain, path] = parts[0].split(')', 1) if self.count is None: self.count = SurtDomainCount(surt_domain) if surt_domain != self.count.surt_domain: # output accumulated statistics for one SURT domain for pair in self.count.output(self.crawl, self.options.exact_counts, self.min_surt_hll_size): yield pair self.urls_total += self.count.unique_urls() for url, cnt in self.count.url.items(): self.urls_hll.add(url) self.url_histogram[cnt] += 1 for digest in self.count.digest: self.digest_hll.add(digest) self.pages_total += self.count.pages self.count = SurtDomainCount(surt_domain) self.min_surt_hll_size = MIN_SURT_HLL_SIZE json_string = ' '.join(parts[2:]) try: metadata = ujson.loads(json_string) self.count.add(path, metadata) except ValueError as e: LOG.error('Failed to parse json: {0} - {1}'.format( e, json_string)) def count_mapper_final(self): self.increment_counter('cdx-stats', 'cdx lines read', self.fetches_total % 1000) if self.count is None: return for pair in self.count.output(self.crawl, self.options.exact_counts, 1): yield pair self.urls_total += self.count.unique_urls() for url, cnt in self.count.url.items(): self.urls_hll.add(url) self.url_histogram[cnt] += 1 for digest in self.count.digest: self.digest_hll.add(digest) self.pages_total += self.count.pages if not self.options.exact_counts: for count, frequency in self.url_histogram.items(): yield((CST.histogram.value, CST.url.value, self.crawl, CST.page.value, count), frequency) yield (CST.size.value, CST.page.value, self.crawl), self.pages_total yield (CST.size.value, CST.fetch.value, self.crawl), self.fetches_total if not self.options.exact_counts: yield (CST.size.value, CST.url.value, self.crawl), self.urls_total yield((CST.size_estimate.value, CST.url.value, self.crawl), CrawlStatsJSONEncoder.json_encode_hyperloglog(self.urls_hll)) yield((CST.size_estimate.value, CST.digest.value, self.crawl), CrawlStatsJSONEncoder.json_encode_hyperloglog(self.digest_hll)) self.increment_counter('cdx-stats', 'cdx files finished', 1) def reducer_init(self): self.counters = Counter() self.mostfrequent = defaultdict(list) def count_reducer(self, key, values): outputType = key[0] if outputType in (CST.size.value, CST.size_robotstxt.value): yield key, sum(values) elif outputType == CST.histogram.value: yield key, sum(values) elif outputType in (CST.url.value, CST.digest.value): # only with --exact-counts crawls = MonthlyCrawlSet() new_crawls = set() page_count = MultiCount(2) for val in values: if type(val) is list: if (outputType == CST.url.value): (crawl, pages) = val page_count.incr(crawl, pages, 1) else: # digest (crawl, (pages, urls)) = val page_count.incr(crawl, pages, urls) crawls.add(crawl) new_crawls.add(crawl) else: # crawl set bit mask crawls.update(val) yield key, crawls.get_bits() for new_crawl in new_crawls: if crawls.is_new(new_crawl): self.counters[(CST.new_items.value, outputType, new_crawl)] += 1 # url/digest duplicate histograms for crawl, counts in page_count.items(): items = (1+counts[0]-counts[1]) self.counters[(CST.histogram.value, outputType, crawl, CST.page.value, items)] += 1 # size in terms of unique URLs and unique content digests for crawl, counts in page_count.items(): self.counters[(CST.size.value, outputType, crawl)] += 1 elif outputType in (CST.mimetype.value, CST.mimetype_detected.value, CST.charset.value, CST.languages.value, CST.primary_language.value, CST.scheme.value, CST.tld.value, CST.domain.value, CST.surt_domain.value, CST.host.value, CST.http_status.value, CST.robotstxt_status.value): yield key, MultiCount.sum_values(values) elif outputType == CST.size_estimate.value: hll = HyperLogLog(HYPERLOGLOG_ERROR) for val in values: hll.update( CrawlStatsJSONDecoder.json_decode_hyperloglog(val)) yield(key, CrawlStatsJSONEncoder.json_encode_hyperloglog(hll)) elif outputType == CST.size_estimate_for.value: res = None hll = None cnt = 0 for val in values: if res: if hll is None: cnt = res[0] hll = CrawlStatsJSONDecoder.json_decode_hyperloglog(res[1]) cnt += val[0] hll.update(CrawlStatsJSONDecoder.json_decode_hyperloglog(val[1])) else: res = val if hll is not None and cnt >= MIN_SURT_HLL_SIZE: yield(key, (cnt, CrawlStatsJSONEncoder.json_encode_hyperloglog(hll))) elif res[0] >= MIN_SURT_HLL_SIZE: yield(key, res) else: raise UnhandledTypeError(outputType) def stats_mapper_init(self): self.counters = Counter() def stats_mapper(self, key, value): if key[0] in (CST.url.value, CST.digest.value, CST.size_estimate_for.value): return if ((self.options.min_domain_frequency > 1) and (key[0] in (CST.host.value, CST.domain.value, CST.surt_domain.value))): # quick skip of infrequent host and domains, # significantly limits amount of tuples processed in reducer page_count = MultiCount.get_count(0, value) url_count = MultiCount.get_count(1, value) self.counters[(CST.size.value, key[0], key[2])] += 1 self.counters[(CST.histogram.value, key[0], key[2], CST.page.value, page_count)] += 1 self.counters[(CST.histogram.value, key[0], key[2], CST.url.value, url_count)] += 1 if key[0] in (CST.domain.value, CST.surt_domain.value): host_count = MultiCount.get_count(2, value) self.counters[(CST.histogram.value, key[0], key[2], CST.host.value, host_count)] += 1 if url_count < self.options.min_domain_frequency: return if key[0] == CST.languages.value: # yield only frequent language combinations (if configured) page_count = MultiCount.get_count(0, value) if ((self.options.min_lang_comb_freq > 1) and (page_count < self.options.min_lang_comb_freq) and (',' in key[1])): return yield key, value def stats_mapper_final(self): for (counter, count) in self.counters.items(): yield counter, count def stats_reducer(self, key, values): outputType = CST(key[0]) item = key[1] crawl = MonthlyCrawl.to_name(key[2]) if outputType in (CST.size, CST.new_items, CST.size_estimate, CST.size_robotstxt): verbose_key = (outputType.name, CST(item).name, crawl) if outputType in (CST.size, CST.size_robotstxt): val = sum(values) elif outputType == CST.new_items: val = MultiCount.sum_values(values) elif outputType == CST.size_estimate: # already "reduced" in count job for val in values: break yield verbose_key, val elif outputType == CST.histogram: yield((outputType.name, CST(item).name, crawl, CST(key[3]).name, key[4]), sum(values)) elif outputType in (CST.mimetype, CST.mimetype_detected, CST.charset, CST.languages, CST.primary_language, CST.scheme, CST.surt_domain, CST.tld, CST.domain, CST.host, CST.http_status, CST.robotstxt_status): item = key[1] for counts in values: page_count = MultiCount.get_count(0, counts) url_count = MultiCount.get_count(1, counts) if outputType in (CST.domain, CST.surt_domain, CST.tld): host_count = MultiCount.get_count(2, counts) if (self.options.min_domain_frequency <= 1 or outputType not in (CST.host, CST.domain, CST.surt_domain)): self.counters[(CST.size.name, outputType.name, crawl)] += 1 self.counters[(CST.histogram.name, outputType.name, crawl, CST.page.name, page_count)] += 1 self.counters[(CST.histogram.name, outputType.name, crawl, CST.url.name, url_count)] += 1 if outputType in (CST.domain, CST.surt_domain, CST.tld): self.counters[(CST.histogram.name, outputType.name, crawl, CST.host.name, host_count)] += 1 if outputType == CST.tld: domain_count = MultiCount.get_count(3, counts) self.counters[(CST.histogram.name, outputType.name, crawl, CST.domain.name, domain_count)] += 1 if outputType in (CST.domain, CST.host, CST.surt_domain): outKey = (outputType.name, crawl) outVal = (page_count, url_count, item) if outputType in (CST.domain, CST.surt_domain): outVal = (page_count, url_count, host_count, item) # take most common if len(self.mostfrequent[outKey]) < self.options.max_hosts: heapq.heappush(self.mostfrequent[outKey], outVal) else: heapq.heappushpop(self.mostfrequent[outKey], outVal) else: yield((outputType.name, item, crawl), counts) else: raise UnhandledTypeError(outputType) def reducer_final(self): for (counter, count) in self.counters.items(): yield counter, count for key, mostfrequent in self.mostfrequent.items(): (outputType, crawl) = key if outputType in (CST.domain.name, CST.surt_domain.name): for (pages, urls, hosts, item) in mostfrequent: yield((outputType, item, crawl), MultiCount.compress(3, [pages, urls, hosts])) else: for (pages, urls, item) in mostfrequent: yield((outputType, item, crawl), MultiCount.compress(2, [pages, urls])) def steps(self): reduces = 10 cdxminsplitsize = 2**32 # do not split cdx map input files if self.options.exact_counts: # with exact counts need many reducers to aggregate the counts # in reasonable time and to get not too large partitions reduces = 200 count_job = \ MRStep(mapper_init=self.count_mapper_init, mapper=self.count_mapper, mapper_final=self.count_mapper_final, reducer_init=self.reducer_init, reducer=self.count_reducer, reducer_final=self.reducer_final, jobconf={'mapreduce.job.reduces': reduces, 'mapreduce.input.fileinputformat.split.minsize': cdxminsplitsize, 'mapreduce.output.fileoutputformat.compress': "true", 'mapreduce.output.fileoutputformat.compress.codec': 'org.apache.hadoop.io.compress.BZip2Codec'}) stats_job = \ MRStep(mapper_init=self.stats_mapper_init, mapper=self.stats_mapper, mapper_final=self.stats_mapper_final, reducer_init=self.reducer_init, reducer=self.stats_reducer, reducer_final=self.reducer_final, jobconf={'mapreduce.job.reduces': 1, 'mapreduce.output.fileoutputformat.compress': "true", 'mapreduce.output.fileoutputformat.compress.codec': 'org.apache.hadoop.io.compress.GzipCodec'}) if self.options.job_to_run == 'count': return [count_job] if self.options.job_to_run == 'stats': return [stats_job] return [count_job, stats_job] if __name__ == '__main__': CCStatsJob.run()