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253 lines
21 KiB
Plaintext
253 lines
21 KiB
Plaintext
How to create dataset from raw data
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===================================
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Look at https://github.com/toddwschneider/nyc-taxi-data
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and http://tech.marksblogg.com/billion-nyc-taxi-rides-redshift.html
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for description of the dataset and loading instructions.
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Data will download to ~227 GB of uncompressed CSV files. It takes about one hour on 1 Gbit connection.
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(Parallel download from s3.amazonaws.com saturate at least half of one gigabit.)
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Some files could be downloaded incompletely. Look at suspicious file sizes and repeat downloading of incomplete files.
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Some files contain broken rows. To correct them, run:
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```
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sed -E '/(.*,){18,}/d' data/yellow_tripdata_2010-02.csv > data/yellow_tripdata_2010-02.csv_
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sed -E '/(.*,){18,}/d' data/yellow_tripdata_2010-03.csv > data/yellow_tripdata_2010-03.csv_
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mv data/yellow_tripdata_2010-02.csv_ data/yellow_tripdata_2010-02.csv
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mv data/yellow_tripdata_2010-03.csv_ data/yellow_tripdata_2010-03.csv
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```
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Then data must be preprocessed inside PostgreSQL. It will do point-in-polygon lookups (map points to areas of New York), and finally JOIN all data to single denormalized flat table. You must install PostgreSQL with PostGIS support.
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When running `initialize_database.sh` script, be careful and check manually, that all tables get created successfully.
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Processing of each month of yellow taxi data in PostgreSQL takes about 20-30 minutes, about 48 hours in total.
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Check exact amount of loaded rows:
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```
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time psql nyc-taxi-data -c "SELECT count(*) FROM trips;"
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count
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------------
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1298979494
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(1 row)
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real 7m9.164s
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```
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(this is slightly more than 1.1 billion rows reported by Mark Litwintschik in a series of blog posts)
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Data in PostgreSQL takes 370 GB (346 GiB).
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Export data from PostgreSQL:
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```
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COPY
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(
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SELECT trips.id,
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trips.vendor_id,
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trips.pickup_datetime,
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trips.dropoff_datetime,
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trips.store_and_fwd_flag,
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trips.rate_code_id,
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trips.pickup_longitude,
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trips.pickup_latitude,
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trips.dropoff_longitude,
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trips.dropoff_latitude,
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trips.passenger_count,
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trips.trip_distance,
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trips.fare_amount,
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trips.extra,
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trips.mta_tax,
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trips.tip_amount,
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trips.tolls_amount,
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trips.ehail_fee,
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trips.improvement_surcharge,
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trips.total_amount,
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trips.payment_type,
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trips.trip_type,
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trips.pickup,
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trips.dropoff,
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cab_types.type cab_type,
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weather.precipitation_tenths_of_mm rain,
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weather.snow_depth_mm,
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weather.snowfall_mm,
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weather.max_temperature_tenths_degrees_celsius max_temp,
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weather.min_temperature_tenths_degrees_celsius min_temp,
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weather.average_wind_speed_tenths_of_meters_per_second wind,
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pick_up.gid pickup_nyct2010_gid,
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pick_up.ctlabel pickup_ctlabel,
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pick_up.borocode pickup_borocode,
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pick_up.boroname pickup_boroname,
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pick_up.ct2010 pickup_ct2010,
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pick_up.boroct2010 pickup_boroct2010,
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pick_up.cdeligibil pickup_cdeligibil,
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pick_up.ntacode pickup_ntacode,
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pick_up.ntaname pickup_ntaname,
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pick_up.puma pickup_puma,
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drop_off.gid dropoff_nyct2010_gid,
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drop_off.ctlabel dropoff_ctlabel,
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drop_off.borocode dropoff_borocode,
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drop_off.boroname dropoff_boroname,
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drop_off.ct2010 dropoff_ct2010,
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drop_off.boroct2010 dropoff_boroct2010,
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drop_off.cdeligibil dropoff_cdeligibil,
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drop_off.ntacode dropoff_ntacode,
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drop_off.ntaname dropoff_ntaname,
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drop_off.puma dropoff_puma
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FROM trips
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LEFT JOIN cab_types
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ON trips.cab_type_id = cab_types.id
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LEFT JOIN central_park_weather_observations_raw weather
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ON weather.date = trips.pickup_datetime::date
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LEFT JOIN nyct2010 pick_up
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ON pick_up.gid = trips.pickup_nyct2010_gid
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LEFT JOIN nyct2010 drop_off
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ON drop_off.gid = trips.dropoff_nyct2010_gid
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) TO '/opt/milovidov/nyc-taxi-data/trips.tsv';
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```
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Dump is created at speed about 50 MB/sec. While creating dump, PostgreSQL reads data from disk at about 28 MB/sec.
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It takes about 5 hours. Resulting tsv file is 590 612 904 969 bytes.
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Create temporary table in ClickHouse:
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```
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CREATE TABLE trips
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(
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trip_id UInt32,
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vendor_id String,
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pickup_datetime DateTime,
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dropoff_datetime Nullable(DateTime),
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store_and_fwd_flag Nullable(FixedString(1)),
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rate_code_id Nullable(UInt8),
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pickup_longitude Nullable(Float64),
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pickup_latitude Nullable(Float64),
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dropoff_longitude Nullable(Float64),
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dropoff_latitude Nullable(Float64),
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passenger_count Nullable(UInt8),
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trip_distance Nullable(Float64),
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fare_amount Nullable(Float32),
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extra Nullable(Float32),
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mta_tax Nullable(Float32),
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tip_amount Nullable(Float32),
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tolls_amount Nullable(Float32),
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ehail_fee Nullable(Float32),
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improvement_surcharge Nullable(Float32),
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total_amount Nullable(Float32),
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payment_type Nullable(String),
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trip_type Nullable(UInt8),
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pickup Nullable(String),
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dropoff Nullable(String),
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cab_type Nullable(String),
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precipitation Nullable(UInt8),
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snow_depth Nullable(UInt8),
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snowfall Nullable(UInt8),
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max_temperature Nullable(UInt8),
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min_temperature Nullable(UInt8),
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average_wind_speed Nullable(UInt8),
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pickup_nyct2010_gid Nullable(UInt8),
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pickup_ctlabel Nullable(String),
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pickup_borocode Nullable(UInt8),
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pickup_boroname Nullable(String),
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pickup_ct2010 Nullable(String),
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pickup_boroct2010 Nullable(String),
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pickup_cdeligibil Nullable(FixedString(1)),
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pickup_ntacode Nullable(String),
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pickup_ntaname Nullable(String),
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pickup_puma Nullable(String),
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dropoff_nyct2010_gid Nullable(UInt8),
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dropoff_ctlabel Nullable(String),
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dropoff_borocode Nullable(UInt8),
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dropoff_boroname Nullable(String),
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dropoff_ct2010 Nullable(String),
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dropoff_boroct2010 Nullable(String),
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dropoff_cdeligibil Nullable(String),
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dropoff_ntacode Nullable(String),
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dropoff_ntaname Nullable(String),
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dropoff_puma Nullable(String)
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) ENGINE = Log;
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```
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This table is needed to select better data types for fields, and if possible, get rid of NULLs.
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```
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time clickhouse-client --query="INSERT INTO trips FORMAT TabSeparated" < trips.tsv
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real 75m56.214s
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```
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Data is read at 112-140 MB/sec.
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Loading data into Log table in single thread took 76 minutes.
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Data inside Log table takes 142 GB.
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(You could also import data directly from Postgres, using `COPY ... TO PROGRAM`.)
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Sadly, all weather-related fields (precipitation...average_wind_speed) are NULLs. We will omit them from final dataset.
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Create and fill final table:
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```
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CREATE TABLE trips_mergetree
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ENGINE = MergeTree(pickup_date, pickup_datetime, 8192)
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AS SELECT
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trip_id,
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CAST(vendor_id AS Enum8('1' = 1, '2' = 2, 'CMT' = 3, 'VTS' = 4, 'DDS' = 5, 'B02512' = 10, 'B02598' = 11, 'B02617' = 12, 'B02682' = 13, 'B02764' = 14)) AS vendor_id,
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toDate(pickup_datetime) AS pickup_date,
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ifNull(pickup_datetime, toDateTime(0)) AS pickup_datetime,
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toDate(dropoff_datetime) AS dropoff_date,
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ifNull(dropoff_datetime, toDateTime(0)) AS dropoff_datetime,
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assumeNotNull(store_and_fwd_flag) IN ('Y', '1', '2') AS store_and_fwd_flag,
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assumeNotNull(rate_code_id) AS rate_code_id,
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assumeNotNull(pickup_longitude) AS pickup_longitude,
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assumeNotNull(pickup_latitude) AS pickup_latitude,
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assumeNotNull(dropoff_longitude) AS dropoff_longitude,
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assumeNotNull(dropoff_latitude) AS dropoff_latitude,
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assumeNotNull(passenger_count) AS passenger_count,
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assumeNotNull(trip_distance) AS trip_distance,
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assumeNotNull(fare_amount) AS fare_amount,
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assumeNotNull(extra) AS extra,
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assumeNotNull(mta_tax) AS mta_tax,
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assumeNotNull(tip_amount) AS tip_amount,
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assumeNotNull(tolls_amount) AS tolls_amount,
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assumeNotNull(ehail_fee) AS ehail_fee,
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assumeNotNull(improvement_surcharge) AS improvement_surcharge,
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assumeNotNull(total_amount) AS total_amount,
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CAST((assumeNotNull(payment_type) AS pt) IN ('CSH', 'CASH', 'Cash', 'CAS', 'Cas', '1') ? 'CSH' : (pt IN ('CRD', 'Credit', 'Cre', 'CRE', 'CREDIT', '2') ? 'CRE' : (pt IN ('NOC', 'No Charge', 'No', '3') ? 'NOC' : (pt IN ('DIS', 'Dispute', 'Dis', '4') ? 'DIS' : 'UNK'))) AS Enum8('CSH' = 1, 'CRE' = 2, 'UNK' = 0, 'NOC' = 3, 'DIS' = 4)) AS payment_type_,
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assumeNotNull(trip_type) AS trip_type,
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ifNull(toFixedString(unhex(pickup), 25), toFixedString('', 25)) AS pickup,
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ifNull(toFixedString(unhex(dropoff), 25), toFixedString('', 25)) AS dropoff,
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CAST(assumeNotNull(cab_type) AS Enum8('yellow' = 1, 'green' = 2, 'uber' = 3)) AS cab_type,
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assumeNotNull(pickup_nyct2010_gid) AS pickup_nyct2010_gid,
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toFloat32(ifNull(pickup_ctlabel, '0')) AS pickup_ctlabel,
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assumeNotNull(pickup_borocode) AS pickup_borocode,
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CAST(assumeNotNull(pickup_boroname) AS Enum8('Manhattan' = 1, 'Queens' = 4, 'Brooklyn' = 3, '' = 0, 'Bronx' = 2, 'Staten Island' = 5)) AS pickup_boroname,
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toFixedString(ifNull(pickup_ct2010, '000000'), 6) AS pickup_ct2010,
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toFixedString(ifNull(pickup_boroct2010, '0000000'), 7) AS pickup_boroct2010,
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CAST(assumeNotNull(ifNull(pickup_cdeligibil, ' ')) AS Enum8(' ' = 0, 'E' = 1, 'I' = 2)) AS pickup_cdeligibil,
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toFixedString(ifNull(pickup_ntacode, '0000'), 4) AS pickup_ntacode,
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CAST(assumeNotNull(pickup_ntaname) AS Enum16('' = 0, 'Airport' = 1, 'Allerton-Pelham Gardens' = 2, 'Annadale-Huguenot-Prince\'s Bay-Eltingville' = 3, 'Arden Heights' = 4, 'Astoria' = 5, 'Auburndale' = 6, 'Baisley Park' = 7, 'Bath Beach' = 8, 'Battery Park City-Lower Manhattan' = 9, 'Bay Ridge' = 10, 'Bayside-Bayside Hills' = 11, 'Bedford' = 12, 'Bedford Park-Fordham North' = 13, 'Bellerose' = 14, 'Belmont' = 15, 'Bensonhurst East' = 16, 'Bensonhurst West' = 17, 'Borough Park' = 18, 'Breezy Point-Belle Harbor-Rockaway Park-Broad Channel' = 19, 'Briarwood-Jamaica Hills' = 20, 'Brighton Beach' = 21, 'Bronxdale' = 22, 'Brooklyn Heights-Cobble Hill' = 23, 'Brownsville' = 24, 'Bushwick North' = 25, 'Bushwick South' = 26, 'Cambria Heights' = 27, 'Canarsie' = 28, 'Carroll Gardens-Columbia Street-Red Hook' = 29, 'Central Harlem North-Polo Grounds' = 30, 'Central Harlem South' = 31, 'Charleston-Richmond Valley-Tottenville' = 32, 'Chinatown' = 33, 'Claremont-Bathgate' = 34, 'Clinton' = 35, 'Clinton Hill' = 36, 'Co-op City' = 37, 'College Point' = 38, 'Corona' = 39, 'Crotona Park East' = 40, 'Crown Heights North' = 41, 'Crown Heights South' = 42, 'Cypress Hills-City Line' = 43, 'DUMBO-Vinegar Hill-Downtown Brooklyn-Boerum Hill' = 44, 'Douglas Manor-Douglaston-Little Neck' = 45, 'Dyker Heights' = 46, 'East Concourse-Concourse Village' = 47, 'East Elmhurst' = 48, 'East Flatbush-Farragut' = 49, 'East Flushing' = 50, 'East Harlem North' = 51, 'East Harlem South' = 52, 'East New York' = 53, 'East New York (Pennsylvania Ave)' = 54, 'East Tremont' = 55, 'East Village' = 56, 'East Williamsburg' = 57, 'Eastchester-Edenwald-Baychester' = 58, 'Elmhurst' = 59, 'Elmhurst-Maspeth' = 60, 'Erasmus' = 61, 'Far Rockaway-Bayswater' = 62, 'Flatbush' = 63, 'Flatlands' = 64, 'Flushing' = 65, 'Fordham South' = 66, 'Forest Hills' = 67, 'Fort Greene' = 68, 'Fresh Meadows-Utopia' = 69, 'Ft. Totten-Bay Terrace-Clearview' = 70, 'Georgetown-Marine Park-Bergen Beach-Mill Basin' = 71, 'Glen Oaks-Floral Park-New Hyde Park' = 72, 'Glendale' = 73, 'Gramercy' = 74, 'Grasmere-Arrochar-Ft. Wadsworth' = 75, 'Gravesend' = 76, 'Great Kills' = 77, 'Greenpoint' = 78, 'Grymes Hill-Clifton-Fox Hills' = 79, 'Hamilton Heights' = 80, 'Hammels-Arverne-Edgemere' = 81, 'Highbridge' = 82, 'Hollis' = 83, 'Homecrest' = 84, 'Hudson Yards-Chelsea-Flatiron-Union Square' = 85, 'Hunters Point-Sunnyside-West Maspeth' = 86, 'Hunts Point' = 87, 'Jackson Heights' = 88, 'Jamaica' = 89, 'Jamaica Estates-Holliswood' = 90, 'Kensington-Ocean Parkway' = 91, 'Kew Gardens' = 92, 'Kew Gardens Hills' = 93, 'Kingsbridge Heights' = 94, 'Laurelton' = 95, 'Lenox Hill-Roosevelt Island' = 96, 'Lincoln Square' = 97, 'Lindenwood-Howard Beach' = 98, 'Longwood' = 99, 'Lower East Side' = 100, 'Madison' = 101, 'Manhattanville' = 102, 'Marble Hill-Inwood' = 103, 'Mariner\'s Harbor-Arlington-Port Ivory-Graniteville' = 104, 'Maspeth' = 105, 'Melrose South-Mott Haven North' = 106, 'Middle Village' = 107, 'Midtown-Midtown South' = 108, 'Midwood' = 109, 'Morningside Heights' = 110, 'Morrisania-Melrose' = 111, 'Mott Haven-Port Morris' = 112, 'Mount Hope' = 113, 'Murray Hill' = 114, 'Murray Hill-Kips Bay' = 115, 'New Brighton-Silver Lake' = 116, 'New Dorp-Midland Beach' = 117, 'New Springville-Bloomfield-Travis' = 118, 'North Corona' = 119, 'North Riverdale-Fieldston-Riverdale' = 120, 'North Side-South Side' = 121, 'Norwood' = 122, 'Oakland Gardens' = 123, 'Oakwood-Oakwood Beach' = 124, 'Ocean Hill' = 125, 'Ocean Parkway South' = 126, 'Old Astoria' = 127, 'Old Town-Dongan Hills-South Beach' = 128, 'Ozone Park' = 129, 'Park Slope-Gowanus' = 130, 'Parkchester' = 131, 'Pelham Bay-Country Club-City Island' = 132, 'Pelham Parkway' = 133, 'Pomonok-Flushing Heights-Hillcrest' = 134, 'Port Richmond' = 135, 'Prospect Heights' = 136, 'Prospect Lefferts Gardens-Wingate' = 137, 'Queens Village' = 138, 'Queensboro Hill' = 139, 'Queensbridge-Ravenswood-Long Island City' = 140, 'Rego Park' = 141, 'Richmond Hill' = 142, 'Ridgewood' = 143, 'Rikers Island' = 144, 'Rosedale' = 145, 'Rossville-Woodrow' = 146, 'Rugby-Remsen Village' = 147, 'Schuylerville-Throgs Neck-Edgewater Park' = 148, 'Seagate-Coney Island' = 149, 'Sheepshead Bay-Gerritsen Beach-Manhattan Beach' = 150, 'SoHo-TriBeCa-Civic Center-Little Italy' = 151, 'Soundview-Bruckner' = 152, 'Soundview-Castle Hill-Clason Point-Harding Park' = 153, 'South Jamaica' = 154, 'South Ozone Park' = 155, 'Springfield Gardens North' = 156, 'Springfield Gardens South-Brookville' = 157, 'Spuyten Duyvil-Kingsbridge' = 158, 'St. Albans' = 159, 'Stapleton-Rosebank' = 160, 'Starrett City' = 161, 'Steinway' = 162, 'Stuyvesant Heights' = 163, 'Stuyvesant Town-Cooper Village' = 164, 'Sunset Park East' = 165, 'Sunset Park West' = 166, 'Todt Hill-Emerson Hill-Heartland Village-Lighthouse Hill' = 167, 'Turtle Bay-East Midtown' = 168, 'University Heights-Morris Heights' = 169, 'Upper East Side-Carnegie Hill' = 170, 'Upper West Side' = 171, 'Van Cortlandt Village' = 172, 'Van Nest-Morris Park-Westchester Square' = 173, 'Washington Heights North' = 174, 'Washington Heights South' = 175, 'West Brighton' = 176, 'West Concourse' = 177, 'West Farms-Bronx River' = 178, 'West New Brighton-New Brighton-St. George' = 179, 'West Village' = 180, 'Westchester-Unionport' = 181, 'Westerleigh' = 182, 'Whitestone' = 183, 'Williamsbridge-Olinville' = 184, 'Williamsburg' = 185, 'Windsor Terrace' = 186, 'Woodhaven' = 187, 'Woodlawn-Wakefield' = 188, 'Woodside' = 189, 'Yorkville' = 190, 'park-cemetery-etc-Bronx' = 191, 'park-cemetery-etc-Brooklyn' = 192, 'park-cemetery-etc-Manhattan' = 193, 'park-cemetery-etc-Queens' = 194, 'park-cemetery-etc-Staten Island' = 195)) AS pickup_ntaname,
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toUInt16(ifNull(pickup_puma, '0')) AS pickup_puma,
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assumeNotNull(dropoff_nyct2010_gid) AS dropoff_nyct2010_gid,
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toFloat32(ifNull(dropoff_ctlabel, '0')) AS dropoff_ctlabel,
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assumeNotNull(dropoff_borocode) AS dropoff_borocode,
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CAST(assumeNotNull(dropoff_boroname) AS Enum8('Manhattan' = 1, 'Queens' = 4, 'Brooklyn' = 3, '' = 0, 'Bronx' = 2, 'Staten Island' = 5)) AS dropoff_boroname,
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toFixedString(ifNull(dropoff_ct2010, '000000'), 6) AS dropoff_ct2010,
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toFixedString(ifNull(dropoff_boroct2010, '0000000'), 7) AS dropoff_boroct2010,
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CAST(assumeNotNull(ifNull(dropoff_cdeligibil, ' ')) AS Enum8(' ' = 0, 'E' = 1, 'I' = 2)) AS dropoff_cdeligibil,
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toFixedString(ifNull(dropoff_ntacode, '0000'), 4) AS dropoff_ntacode,
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CAST(assumeNotNull(dropoff_ntaname) AS Enum16('' = 0, 'Airport' = 1, 'Allerton-Pelham Gardens' = 2, 'Annadale-Huguenot-Prince\'s Bay-Eltingville' = 3, 'Arden Heights' = 4, 'Astoria' = 5, 'Auburndale' = 6, 'Baisley Park' = 7, 'Bath Beach' = 8, 'Battery Park City-Lower Manhattan' = 9, 'Bay Ridge' = 10, 'Bayside-Bayside Hills' = 11, 'Bedford' = 12, 'Bedford Park-Fordham North' = 13, 'Bellerose' = 14, 'Belmont' = 15, 'Bensonhurst East' = 16, 'Bensonhurst West' = 17, 'Borough Park' = 18, 'Breezy Point-Belle Harbor-Rockaway Park-Broad Channel' = 19, 'Briarwood-Jamaica Hills' = 20, 'Brighton Beach' = 21, 'Bronxdale' = 22, 'Brooklyn Heights-Cobble Hill' = 23, 'Brownsville' = 24, 'Bushwick North' = 25, 'Bushwick South' = 26, 'Cambria Heights' = 27, 'Canarsie' = 28, 'Carroll Gardens-Columbia Street-Red Hook' = 29, 'Central Harlem North-Polo Grounds' = 30, 'Central Harlem South' = 31, 'Charleston-Richmond Valley-Tottenville' = 32, 'Chinatown' = 33, 'Claremont-Bathgate' = 34, 'Clinton' = 35, 'Clinton Hill' = 36, 'Co-op City' = 37, 'College Point' = 38, 'Corona' = 39, 'Crotona Park East' = 40, 'Crown Heights North' = 41, 'Crown Heights South' = 42, 'Cypress Hills-City Line' = 43, 'DUMBO-Vinegar Hill-Downtown Brooklyn-Boerum Hill' = 44, 'Douglas Manor-Douglaston-Little Neck' = 45, 'Dyker Heights' = 46, 'East Concourse-Concourse Village' = 47, 'East Elmhurst' = 48, 'East Flatbush-Farragut' = 49, 'East Flushing' = 50, 'East Harlem North' = 51, 'East Harlem South' = 52, 'East New York' = 53, 'East New York (Pennsylvania Ave)' = 54, 'East Tremont' = 55, 'East Village' = 56, 'East Williamsburg' = 57, 'Eastchester-Edenwald-Baychester' = 58, 'Elmhurst' = 59, 'Elmhurst-Maspeth' = 60, 'Erasmus' = 61, 'Far Rockaway-Bayswater' = 62, 'Flatbush' = 63, 'Flatlands' = 64, 'Flushing' = 65, 'Fordham South' = 66, 'Forest Hills' = 67, 'Fort Greene' = 68, 'Fresh Meadows-Utopia' = 69, 'Ft. Totten-Bay Terrace-Clearview' = 70, 'Georgetown-Marine Park-Bergen Beach-Mill Basin' = 71, 'Glen Oaks-Floral Park-New Hyde Park' = 72, 'Glendale' = 73, 'Gramercy' = 74, 'Grasmere-Arrochar-Ft. Wadsworth' = 75, 'Gravesend' = 76, 'Great Kills' = 77, 'Greenpoint' = 78, 'Grymes Hill-Clifton-Fox Hills' = 79, 'Hamilton Heights' = 80, 'Hammels-Arverne-Edgemere' = 81, 'Highbridge' = 82, 'Hollis' = 83, 'Homecrest' = 84, 'Hudson Yards-Chelsea-Flatiron-Union Square' = 85, 'Hunters Point-Sunnyside-West Maspeth' = 86, 'Hunts Point' = 87, 'Jackson Heights' = 88, 'Jamaica' = 89, 'Jamaica Estates-Holliswood' = 90, 'Kensington-Ocean Parkway' = 91, 'Kew Gardens' = 92, 'Kew Gardens Hills' = 93, 'Kingsbridge Heights' = 94, 'Laurelton' = 95, 'Lenox Hill-Roosevelt Island' = 96, 'Lincoln Square' = 97, 'Lindenwood-Howard Beach' = 98, 'Longwood' = 99, 'Lower East Side' = 100, 'Madison' = 101, 'Manhattanville' = 102, 'Marble Hill-Inwood' = 103, 'Mariner\'s Harbor-Arlington-Port Ivory-Graniteville' = 104, 'Maspeth' = 105, 'Melrose South-Mott Haven North' = 106, 'Middle Village' = 107, 'Midtown-Midtown South' = 108, 'Midwood' = 109, 'Morningside Heights' = 110, 'Morrisania-Melrose' = 111, 'Mott Haven-Port Morris' = 112, 'Mount Hope' = 113, 'Murray Hill' = 114, 'Murray Hill-Kips Bay' = 115, 'New Brighton-Silver Lake' = 116, 'New Dorp-Midland Beach' = 117, 'New Springville-Bloomfield-Travis' = 118, 'North Corona' = 119, 'North Riverdale-Fieldston-Riverdale' = 120, 'North Side-South Side' = 121, 'Norwood' = 122, 'Oakland Gardens' = 123, 'Oakwood-Oakwood Beach' = 124, 'Ocean Hill' = 125, 'Ocean Parkway South' = 126, 'Old Astoria' = 127, 'Old Town-Dongan Hills-South Beach' = 128, 'Ozone Park' = 129, 'Park Slope-Gowanus' = 130, 'Parkchester' = 131, 'Pelham Bay-Country Club-City Island' = 132, 'Pelham Parkway' = 133, 'Pomonok-Flushing Heights-Hillcrest' = 134, 'Port Richmond' = 135, 'Prospect Heights' = 136, 'Prospect Lefferts Gardens-Wingate' = 137, 'Queens Village' = 138, 'Queensboro Hill' = 139, 'Queensbridge-Ravenswood-Long Island City' = 140, 'Rego Park' = 141, 'Richmond Hill' = 142, 'Ridgewood' = 143, 'Rikers Island' = 144, 'Rosedale' = 145, 'Rossville-Woodrow' = 146, 'Rugby-Remsen Village' = 147, 'Schuylerville-Throgs Neck-Edgewater Park' = 148, 'Seagate-Coney Island' = 149, 'Sheepshead Bay-Gerritsen Beach-Manhattan Beach' = 150, 'SoHo-TriBeCa-Civic Center-Little Italy' = 151, 'Soundview-Bruckner' = 152, 'Soundview-Castle Hill-Clason Point-Harding Park' = 153, 'South Jamaica' = 154, 'South Ozone Park' = 155, 'Springfield Gardens North' = 156, 'Springfield Gardens South-Brookville' = 157, 'Spuyten Duyvil-Kingsbridge' = 158, 'St. Albans' = 159, 'Stapleton-Rosebank' = 160, 'Starrett City' = 161, 'Steinway' = 162, 'Stuyvesant Heights' = 163, 'Stuyvesant Town-Cooper Village' = 164, 'Sunset Park East' = 165, 'Sunset Park West' = 166, 'Todt Hill-Emerson Hill-Heartland Village-Lighthouse Hill' = 167, 'Turtle Bay-East Midtown' = 168, 'University Heights-Morris Heights' = 169, 'Upper East Side-Carnegie Hill' = 170, 'Upper West Side' = 171, 'Van Cortlandt Village' = 172, 'Van Nest-Morris Park-Westchester Square' = 173, 'Washington Heights North' = 174, 'Washington Heights South' = 175, 'West Brighton' = 176, 'West Concourse' = 177, 'West Farms-Bronx River' = 178, 'West New Brighton-New Brighton-St. George' = 179, 'West Village' = 180, 'Westchester-Unionport' = 181, 'Westerleigh' = 182, 'Whitestone' = 183, 'Williamsbridge-Olinville' = 184, 'Williamsburg' = 185, 'Windsor Terrace' = 186, 'Woodhaven' = 187, 'Woodlawn-Wakefield' = 188, 'Woodside' = 189, 'Yorkville' = 190, 'park-cemetery-etc-Bronx' = 191, 'park-cemetery-etc-Brooklyn' = 192, 'park-cemetery-etc-Manhattan' = 193, 'park-cemetery-etc-Queens' = 194, 'park-cemetery-etc-Staten Island' = 195)) AS dropoff_ntaname,
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toUInt16(ifNull(dropoff_puma, '0')) AS dropoff_puma
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FROM trips
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```
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