Create the Training Feature Vector

train_quantify.sql

WITH train_ordered as (
  select * from training2
  order by rowid asc
), 
train_quantified as (
  select
    t0.rowid,
    t0.sales,
    t2.*,
    t0.competitiondistance
  from
    train_ordered t0 
    -- indexing non-number columns
    LATERAL VIEW quantify(true,
          stateholiday, store, promo, dayofweek, schoolholiday, promo2sinceweek, competitionopensinceyear, assortment, promo2sinceyear, promointerval, promo2, storetype, competitionopensincemonth, year, month, day) t2
       as stateholiday, store, promo, dayofweek, schoolholiday, promo2sinceweek, competitionopensinceyear, assortment, promo2sinceyear, promointerval, promo2, storetype, competitionopensincemonth, year, month, day
)
INSERT OVERWRITE TABLE training3
SELECT
  t1.rowid,
  ARRAY( -- padding zero for missing values
    t1.stateholiday, t1.store, t1.promo, t1.dayofweek, t1.schoolholiday,
    IF(t1.promo2sinceweek IS NULL, 0, t1.promo2sinceweek), 
    IF(t1.competitionopensinceyear IS NULL, 0, t1.competitionopensinceyear), 
    t1.assortment,
    IF(t1.promo2sinceyear IS NULL, 0, t1.promo2sinceyear),
    IF(t1.promointerval IS NULL, 0, t1.promointerval),
    t1.promo2, t1.storetype, 
    IF(t1.competitionopensincemonth IS NULL, 0, t1.competitionopensincemonth),
    t1.year, t1.month, t1.day,
    IF(t1.competitiondistance IS NULL, 0, t1.competitiondistance)
  ) AS features,
  LN(1 + t1.sales) AS label, -- log scale conversion
  t1.sales
FROM
  train_quantified t1
;