y1chi commented on a change in pull request #12580: URL: https://github.com/apache/beam/pull/12580#discussion_r470387263
########## File path: sdks/python/apache_beam/testing/benchmarks/nexmark/models/bids_per_session.py ########## @@ -0,0 +1,56 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +"""Result of Query11 and 12.""" Review comment: ditto ########## File path: sdks/python/apache_beam/testing/benchmarks/nexmark/models/auction_count.py ########## @@ -0,0 +1,56 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +"""Result of Query5.""" +from __future__ import absolute_import + +from apache_beam.coders import coder_impl +from apache_beam.coders.coders import FastCoder +from apache_beam.testing.benchmarks.nexmark import nexmark_util + + +class AuctionCountCoder(FastCoder): + def _create_impl(self): + return AuctionCountCoderImpl() + + def is_deterministic(self): + # type: () -> bool + return True + + +class AuctionCount(object): Review comment: are all the result objects necessary? if it is for validation purpose we should be able to just use a dict and rely on additional script to compare. ########## File path: sdks/python/apache_beam/testing/benchmarks/nexmark/models/auction_count.py ########## @@ -0,0 +1,56 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +"""Result of Query5.""" Review comment: The module document should be more explanatory. ########## File path: sdks/python/apache_beam/testing/benchmarks/nexmark/models/bids_per_session.py ########## @@ -0,0 +1,56 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +"""Result of Query11 and 12.""" +from __future__ import absolute_import + +from apache_beam.coders import coder_impl +from apache_beam.coders.coders import FastCoder +from apache_beam.testing.benchmarks.nexmark import nexmark_util + + +class BidsPerSessionCoder(FastCoder): Review comment: Does every result class need a coder? What are the coder used for? ########## File path: sdks/python/apache_beam/testing/benchmarks/nexmark/queries/query3.py ########## @@ -0,0 +1,164 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +""" +Query 3, 'Local Item Suggestion'. Who is selling in OR, ID or CA in category +10, and for what auction ids? In CQL syntax:: + + SELECT Istream(P.name, P.city, P.state, A.id) + FROM Auction A [ROWS UNBOUNDED], Person P [ROWS UNBOUNDED] + WHERE A.seller = P.id + AND (P.state = `OR' OR P.state = `ID' OR P.state = `CA') + AND A.category = 10; + +We'll implement this query to allow 'new auction' events to come before the +'new person' events for the auction seller. Those auctions will be stored until +the matching person is seen. Then all subsequent auctions for a person will use +the stored person record. +""" + +from __future__ import absolute_import + +import logging + +import apache_beam as beam +from apache_beam.coders import coders +from apache_beam.testing.benchmarks.nexmark.models import name_city_state_id +from apache_beam.testing.benchmarks.nexmark.models import nexmark_model +from apache_beam.testing.benchmarks.nexmark.queries import nexmark_query_util +from apache_beam.transforms import trigger +from apache_beam.transforms import userstate +from apache_beam.transforms import window +from apache_beam.transforms.userstate import on_timer +from apache_beam.utils.timestamp import Duration + + +def load(events, metadata=None): + num_events_in_pane = 30 + windowed_events = ( + events + | beam.WindowInto( + window.GlobalWindows(), + trigger=trigger.Repeatedly(trigger.AfterCount(num_events_in_pane)), + accumulation_mode=trigger.AccumulationMode.DISCARDING, + allowed_lateness=Duration.of(0))) + auction_by_seller_id = ( + windowed_events + | nexmark_query_util.JustAuctions() + | 'query3_filter_category' >> beam.Filter(lambda auc: auc.category == 10) + | 'query3_key_by_seller' >> beam.ParDo( + nexmark_query_util.AuctionBySellerFn())) + person_by_id = ( + windowed_events + | nexmark_query_util.JustPerson() + | 'query3_filter_region' >> beam.Filter( + lambda person: person.state == 'OR' or person.state == 'ID' or person. + state == 'CA') + | 'query3_key_by_person_id' >> beam.ParDo( + nexmark_query_util.PersonByIdFn())) + return ({ + nexmark_query_util.AUCTION_TAG: auction_by_seller_id, + nexmark_query_util.PERSON_TAG: person_by_id, + } + | beam.CoGroupByKey() + | 'query3_join' >> beam.ParDo( + JoinFn(metadata.get('max_auction_waiting_time'))) + | 'query3_output' >> beam.Map( + lambda t: name_city_state_id.NameCiyStateId( + t[1].name, t[1].city, t[1].state, t[0].id))) + + +class JoinFn(beam.DoFn): + """ + Join auctions and person by person id and emit their product one pair at + a time. + + We know a person may submit any number of auctions. Thus new person event + must have the person record stored in persistent state in order to match + future auctions by that person. + + However we know that each auction is associated with at most one person, so + only need to store auction records in persistent state until we have seen the + corresponding person record. And of course may have already seen that record. + """ + + AUCTIONS = 'auctions_state' + PERSON = 'person_state' + PERSON_EXPIRING = 'person_state_expiring' + + auction_spec = userstate.ReadModifyWriteStateSpec( Review comment: Should this be a BagUserState instead, generally it's better to use BagUserState for iterables. ########## File path: sdks/python/apache_beam/testing/benchmarks/nexmark/queries/query3.py ########## @@ -0,0 +1,164 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +""" +Query 3, 'Local Item Suggestion'. Who is selling in OR, ID or CA in category +10, and for what auction ids? In CQL syntax:: + + SELECT Istream(P.name, P.city, P.state, A.id) + FROM Auction A [ROWS UNBOUNDED], Person P [ROWS UNBOUNDED] + WHERE A.seller = P.id + AND (P.state = `OR' OR P.state = `ID' OR P.state = `CA') + AND A.category = 10; + +We'll implement this query to allow 'new auction' events to come before the +'new person' events for the auction seller. Those auctions will be stored until +the matching person is seen. Then all subsequent auctions for a person will use +the stored person record. +""" + +from __future__ import absolute_import + +import logging + +import apache_beam as beam +from apache_beam.coders import coders +from apache_beam.testing.benchmarks.nexmark.models import name_city_state_id +from apache_beam.testing.benchmarks.nexmark.models import nexmark_model +from apache_beam.testing.benchmarks.nexmark.queries import nexmark_query_util +from apache_beam.transforms import trigger +from apache_beam.transforms import userstate +from apache_beam.transforms import window +from apache_beam.transforms.userstate import on_timer +from apache_beam.utils.timestamp import Duration + + +def load(events, metadata=None): + num_events_in_pane = 30 + windowed_events = ( + events + | beam.WindowInto( + window.GlobalWindows(), + trigger=trigger.Repeatedly(trigger.AfterCount(num_events_in_pane)), + accumulation_mode=trigger.AccumulationMode.DISCARDING, + allowed_lateness=Duration.of(0))) Review comment: by default it should be 0 so this is not necessary. ########## File path: sdks/python/apache_beam/testing/benchmarks/nexmark/queries/query6.py ########## @@ -0,0 +1,93 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +""" +Query 6, 'Average Selling Price by Seller'. Select the average selling price +over the last 10 closed auctions by the same seller. In CQL syntax:: + + SELECT Istream(AVG(Q.final), Q.seller) + FROM (SELECT Rstream(MAX(B.price) AS final, A.seller) + FROM Auction A [ROWS UNBOUNDED], Bid B [ROWS UNBOUNDED] + WHERE A.id=B.auction + AND B.datetime < A.expires AND A.expires < CURRENT_TIME + GROUP BY A.id, A.seller) [PARTITION BY A.seller ROWS 10] Q + GROUP BY Q.seller; +""" + +from __future__ import absolute_import +from __future__ import division + +import apache_beam as beam +from apache_beam.testing.benchmarks.nexmark.models import seller_price +from apache_beam.testing.benchmarks.nexmark.queries import nexmark_query_util +from apache_beam.testing.benchmarks.nexmark.queries import winning_bids +from apache_beam.transforms import trigger +from apache_beam.transforms import window + + +def load(events, metadata=None): + # find winning bids for each closed auction + return ( + events + # find winning bids + | beam.Filter(nexmark_query_util.auction_or_bid) + | winning_bids.WinningBids() + # (auction_bids -> (aution.seller, bid) + | beam.Map(lambda auc_bid: (auc_bid.auction.seller, auc_bid.bid)) + # calculate and output mean as data arrives + | beam.WindowInto( + window.GlobalWindows(), + trigger=trigger.Repeatedly(trigger.AfterCount(1)), + accumulation_mode=trigger.AccumulationMode.ACCUMULATING, + allowed_lateness=0) + # | beam.combiners.Count.Globally()) + | beam.CombinePerKey(MovingMeanSellingPriceFn(10)) + | beam.Map(lambda t: seller_price.SellerPrice(t[0], t[1]))) + + +class MovingMeanSellingPriceFn(beam.CombineFn): + """ + Combiner to keep track of up to max_num_bids of the most recent wining + bids and calculate their average selling price. + """ + def __init__(self, max_num_bids): + self.max_num_bids = max_num_bids + + def create_accumulator(self): + return [] + + def add_input(self, accumulator, element): + accumulator.append(element) + new_accu = sorted(accumulator, key=lambda bid: (bid.date_time, bid.price)) + if len(new_accu) > self.max_num_bids: + del new_accu[0] + return new_accu + + def merge_accumulators(self, accumulators): + new_accu = [] + for accumulator in accumulators: + new_accu += accumulator + new_accu.sort(key=lambda bid: (bid.date_time, bid.price)) + return new_accu[-10:] + + def extract_output(self, accumulator): + if len(accumulator) == 0: + return 0 + sum_price = 0 + for bid in accumulator: Review comment: call sum() directly? ########## File path: sdks/python/apache_beam/testing/benchmarks/nexmark/queries/query6.py ########## @@ -0,0 +1,93 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +""" +Query 6, 'Average Selling Price by Seller'. Select the average selling price +over the last 10 closed auctions by the same seller. In CQL syntax:: + + SELECT Istream(AVG(Q.final), Q.seller) + FROM (SELECT Rstream(MAX(B.price) AS final, A.seller) + FROM Auction A [ROWS UNBOUNDED], Bid B [ROWS UNBOUNDED] + WHERE A.id=B.auction + AND B.datetime < A.expires AND A.expires < CURRENT_TIME + GROUP BY A.id, A.seller) [PARTITION BY A.seller ROWS 10] Q + GROUP BY Q.seller; +""" + +from __future__ import absolute_import +from __future__ import division + +import apache_beam as beam +from apache_beam.testing.benchmarks.nexmark.models import seller_price +from apache_beam.testing.benchmarks.nexmark.queries import nexmark_query_util +from apache_beam.testing.benchmarks.nexmark.queries import winning_bids +from apache_beam.transforms import trigger +from apache_beam.transforms import window + + +def load(events, metadata=None): + # find winning bids for each closed auction + return ( + events + # find winning bids + | beam.Filter(nexmark_query_util.auction_or_bid) + | winning_bids.WinningBids() + # (auction_bids -> (aution.seller, bid) + | beam.Map(lambda auc_bid: (auc_bid.auction.seller, auc_bid.bid)) + # calculate and output mean as data arrives + | beam.WindowInto( + window.GlobalWindows(), + trigger=trigger.Repeatedly(trigger.AfterCount(1)), + accumulation_mode=trigger.AccumulationMode.ACCUMULATING, + allowed_lateness=0) + # | beam.combiners.Count.Globally()) + | beam.CombinePerKey(MovingMeanSellingPriceFn(10)) + | beam.Map(lambda t: seller_price.SellerPrice(t[0], t[1]))) + + +class MovingMeanSellingPriceFn(beam.CombineFn): + """ + Combiner to keep track of up to max_num_bids of the most recent wining + bids and calculate their average selling price. + """ + def __init__(self, max_num_bids): + self.max_num_bids = max_num_bids + + def create_accumulator(self): + return [] + + def add_input(self, accumulator, element): + accumulator.append(element) + new_accu = sorted(accumulator, key=lambda bid: (bid.date_time, bid.price)) + if len(new_accu) > self.max_num_bids: Review comment: should this be a while loop? ########## File path: sdks/python/apache_beam/testing/benchmarks/nexmark/queries/query6.py ########## @@ -0,0 +1,93 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +""" +Query 6, 'Average Selling Price by Seller'. Select the average selling price +over the last 10 closed auctions by the same seller. In CQL syntax:: + + SELECT Istream(AVG(Q.final), Q.seller) + FROM (SELECT Rstream(MAX(B.price) AS final, A.seller) + FROM Auction A [ROWS UNBOUNDED], Bid B [ROWS UNBOUNDED] + WHERE A.id=B.auction + AND B.datetime < A.expires AND A.expires < CURRENT_TIME + GROUP BY A.id, A.seller) [PARTITION BY A.seller ROWS 10] Q + GROUP BY Q.seller; +""" + +from __future__ import absolute_import +from __future__ import division + +import apache_beam as beam +from apache_beam.testing.benchmarks.nexmark.models import seller_price +from apache_beam.testing.benchmarks.nexmark.queries import nexmark_query_util +from apache_beam.testing.benchmarks.nexmark.queries import winning_bids +from apache_beam.transforms import trigger +from apache_beam.transforms import window + + +def load(events, metadata=None): + # find winning bids for each closed auction + return ( + events + # find winning bids + | beam.Filter(nexmark_query_util.auction_or_bid) + | winning_bids.WinningBids() + # (auction_bids -> (aution.seller, bid) + | beam.Map(lambda auc_bid: (auc_bid.auction.seller, auc_bid.bid)) + # calculate and output mean as data arrives + | beam.WindowInto( + window.GlobalWindows(), + trigger=trigger.Repeatedly(trigger.AfterCount(1)), + accumulation_mode=trigger.AccumulationMode.ACCUMULATING, + allowed_lateness=0) + # | beam.combiners.Count.Globally()) Review comment: remove this? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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