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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,41 @@ | ||
| let mc = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, company_id: @vec {int -> int}, company_type_id: @vec {int -> int}, note: @vec {int -> string}, size: int>]("datasets/job/movie_companies.csv") | ||
| let t = load[<id: @vec {int -> int}, title: @vec {int -> string}, imdb_index: @vec {int -> string}, kind_id: @vec {int -> int}, production_year: @vec {int -> int}, imdb_id: @vec {int -> string}, phonetic_code: @vec {int -> string}, episode_of_id: @vec {int -> int}, season_nr: @vec {int -> int}, episode_nr: @vec {int -> int}, series_years: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/10b/t.csv") | ||
| let ct = load[<id: @vec {int -> int}, kind: @vec {int -> string}, size: int>]("datasets/job/company_type.csv") | ||
| let cn = load[<id: @vec {int -> int}, name: @vec {int -> string}, country_code: @vec {int -> string}, imdb_id: @vec {int -> string}, name_pcode_nf: @vec {int -> string}, name_pcode_sf: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/10b/cn.csv") | ||
| let ci = load[<id: @vec {int -> int}, person_id: @vec {int -> int}, movie_id: @vec {int -> int}, person_role_id: @vec {int -> int}, note: @vec {int -> string}, nr_order: @vec {int -> int}, role_id: @vec {int -> int}, size: int>]("datasets/job/10b/ci.csv") | ||
| let rt = load[<id: @vec {int -> int}, role: @vec {int -> string}, size: int>]("datasets/job/10b/rt.csv") | ||
| let chn = load[<id: @vec {int -> int}, name: @vec {int -> string}, imdb_index: @vec {int -> string}, imdb_id: @vec {int -> int}, name_pcode_cf: @vec {int -> string}, surname_pcode: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/char_name.csv") | ||
|
|
||
| let ct_trie0 = sum(<i, _> <- range(ct.size)) @phmap(ct.size) { unique(ct.id(i)) -> 1 } in | ||
| let cn_trie0 = sum(<i, _> <- range(cn.size)) @phmap(cn.size) { unique(cn.id(i)) -> 1 } in | ||
| let t_trie0 = sum(<i, _> <- range(t.size)) @phmap(t.size) { t.id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| let interm0_trie0 = sum(<mc_off, _> <- range(mc.size)) | ||
| let x0 = mc.company_type_id(mc_off) in | ||
| if (x0 ∈ ct_trie0) then | ||
| let ct_trie1 = ct_trie0(x0) in | ||
| let x1 = mc.company_id(mc_off) in | ||
| if (x1 ∈ cn_trie0) then | ||
| let cn_trie1 = cn_trie0(x1) in | ||
| let x2 = mc.movie_id(mc_off) in | ||
| if (x2 ∈ t_trie0) then | ||
| let t_trie1 = t_trie0(x2) in | ||
| sum(<t_off, _> <- t_trie1) | ||
| @phmap(promote[min_sum](1000000) + promote[min_sum](mc.size)) { mc.movie_id(mc_off) -> @smallvecdict(4) { <col1=mc.company_type_id(mc_off), col2=mc.company_id(mc_off), col3=t.title(t_off)> -> 1 } } | ||
| in | ||
|
|
||
| let rt_trie0 = sum(<i, _> <- range(rt.size)) @phmap(rt.size) { unique(rt.id(i)) -> 1 } in | ||
| let chn_trie0 = sum(<i, _> <- range(chn.size)) @phmap(chn.size) { chn.id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| sum(<ci_off, _> <- range(ci.size)) | ||
| let x0 = ci.role_id(ci_off) in | ||
| if (x0 ∈ rt_trie0) then | ||
| let rt_trie1 = rt_trie0(x0) in | ||
| let x1 = ci.movie_id(ci_off) in | ||
| if (x1 ∈ interm0_trie0) then | ||
| let interm0_trie1 = interm0_trie0(x1) in | ||
| let x2 = ci.person_role_id(ci_off) in | ||
| if (x2 ∈ chn_trie0) then | ||
| let chn_trie1 = chn_trie0(x2) in | ||
| let mn_interm0 = sum(<interm0_tuple, _> <- interm0_trie1) promote[min_sum](<col3=interm0_tuple.col3>) in | ||
| let mn_chn = sum(<chn_off, _> <- chn_trie1) promote[min_sum](<name=chn.name(chn_off)>) in | ||
| promote[min_sum](<col5=mn_interm0.col3, col6=mn_chn.name>) | ||
|
|
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,52 @@ | ||
| let t = load[<id: @vec {int -> int}, title: @vec {int -> string}, imdb_index: @vec {int -> string}, kind_id: @vec {int -> int}, production_year: @vec {int -> int}, imdb_id: @vec {int -> string}, phonetic_code: @vec {int -> string}, episode_of_id: @vec {int -> int}, season_nr: @vec {int -> int}, episode_nr: @vec {int -> int}, series_years: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/title.csv") | ||
| let miidx = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, info_type_id: @vec {int -> int}, info: @vec {int -> string}, note: @vec {int -> string}, size: int>]("datasets/job/movie_info_idx.csv") | ||
| let mi = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, info_type_id: @vec {int -> int}, info: @vec {int -> string}, note: @vec {int -> string}, size: int>]("datasets/job/movie_info.csv") | ||
| let mc = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, company_id: @vec {int -> int}, company_type_id: @vec {int -> int}, note: @vec {int -> string}, size: int>]("datasets/job/movie_companies.csv") | ||
| let kt = load[<id: @vec {int -> int}, kind: @vec {int -> string}, size: int>]("datasets/job/13a/kt.csv") | ||
| let it2 = load[<id: @vec {int -> int}, info: @vec {int -> string}, size: int>]("datasets/job/13a/it2.csv") | ||
| let it = load[<id: @vec {int -> int}, info: @vec {int -> string}, size: int>]("datasets/job/13a/it.csv") | ||
| let ct = load[<id: @vec {int -> int}, kind: @vec {int -> string}, size: int>]("datasets/job/13a/ct.csv") | ||
| let cn = load[<id: @vec {int -> int}, name: @vec {int -> string}, country_code: @vec {int -> string}, imdb_id: @vec {int -> string}, name_pcode_nf: @vec {int -> string}, name_pcode_sf: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/13a/cn.csv") | ||
|
|
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| let miidx_trie0 = sum(<i, _> <- range(miidx.size)) @phmap(miidx.size) { miidx.movie_id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| let interm0_trie0 = sum(<t_off, _> <- range(t.size)) | ||
| let x0 = t.id(t_off) in | ||
| if (x0 ∈ miidx_trie0) then | ||
| let miidx_trie1 = miidx_trie0(x0) in | ||
| sum(<miidx_off, _> <- miidx_trie1) | ||
| @phmap(promote[min_sum](1000000) + promote[min_sum](t.size)) { t.id(t_off) -> @smallvecdict(4) { <col1=t.title(t_off), col2=t.kind_id(t_off), col3=miidx.info(miidx_off), col4=miidx.info_type_id(miidx_off)> -> 1 } } | ||
| in | ||
|
|
||
| let mc_trie0 = sum(<i, _> <- range(mc.size)) @phmap(mc.size) { mc.movie_id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| let kt_trie0 = sum(<i, _> <- range(kt.size)) @phmap(kt.size) { unique(kt.id(i)) -> 1 } in | ||
| let it2_trie0 = sum(<i, _> <- range(it2.size)) @phmap(it2.size) { unique(it2.id(i)) -> 1 } in | ||
| let it_trie0 = sum(<i, _> <- range(it.size)) @phmap(it.size) { unique(it.id(i)) -> 1 } in | ||
| let ct_trie0 = sum(<i, _> <- range(ct.size)) @phmap(ct.size) { unique(ct.id(i)) -> 1 } in | ||
| let cn_trie0 = sum(<i, _> <- range(cn.size)) @phmap(cn.size) { unique(cn.id(i)) -> 1 } in | ||
| sum(<mi_off, _> <- range(mi.size)) | ||
| let x0 = mi.movie_id(mi_off) in | ||
| if (x0 ∈ interm0_trie0) then | ||
| if (x0 ∈ mc_trie0) then | ||
| let interm0_trie1 = interm0_trie0(x0) in | ||
| let mc_trie1 = mc_trie0(x0) in | ||
| sum(<interm0_tuple, _> <- interm0_trie1) | ||
| let x1 = interm0_tuple.col2 in | ||
| if (x1 ∈ kt_trie0) then | ||
| let kt_trie1 = kt_trie0(x1) in | ||
| let x2 = mi.info_type_id(mi_off) in | ||
| if (x2 ∈ it2_trie0) then | ||
| let it2_trie1 = it2_trie0(x2) in | ||
| let x3 = interm0_tuple.col4 in | ||
| if (x3 ∈ it_trie0) then | ||
| let it_trie1 = it_trie0(x3) in | ||
| sum(<mc_off, _> <- mc_trie1) | ||
| let x4 = mc.company_type_id(mc_off) in | ||
| if (x4 ∈ ct_trie0) then | ||
| let ct_trie1 = ct_trie0(x4) in | ||
| let x5 = mc.company_id(mc_off) in | ||
| if (x5 ∈ cn_trie0) then | ||
| let cn_trie1 = cn_trie0(x5) in | ||
| let mn_mi = <info=mi.info(mi_off)> in | ||
| let mn_interm0 = <col1=interm0_tuple.col1, col3=interm0_tuple.col3> in | ||
| promote[min_sum](<col2=mn_mi.info, col5=mn_interm0.col1, col6=mn_interm0.col3>) | ||
|
|
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,52 @@ | ||
| let t = load[<id: @vec {int -> int}, title: @vec {int -> string}, imdb_index: @vec {int -> string}, kind_id: @vec {int -> int}, production_year: @vec {int -> int}, imdb_id: @vec {int -> string}, phonetic_code: @vec {int -> string}, episode_of_id: @vec {int -> int}, season_nr: @vec {int -> int}, episode_nr: @vec {int -> int}, series_years: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/title.csv") | ||
| let miidx = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, info_type_id: @vec {int -> int}, info: @vec {int -> string}, note: @vec {int -> string}, size: int>]("datasets/job/movie_info_idx.csv") | ||
| let mi = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, info_type_id: @vec {int -> int}, info: @vec {int -> string}, note: @vec {int -> string}, size: int>]("datasets/job/movie_info.csv") | ||
| let mc = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, company_id: @vec {int -> int}, company_type_id: @vec {int -> int}, note: @vec {int -> string}, size: int>]("datasets/job/movie_companies.csv") | ||
| let kt = load[<id: @vec {int -> int}, kind: @vec {int -> string}, size: int>]("datasets/job/13d/kt.csv") | ||
| let it2 = load[<id: @vec {int -> int}, info: @vec {int -> string}, size: int>]("datasets/job/13d/it2.csv") | ||
| let it = load[<id: @vec {int -> int}, info: @vec {int -> string}, size: int>]("datasets/job/13d/it.csv") | ||
| let ct = load[<id: @vec {int -> int}, kind: @vec {int -> string}, size: int>]("datasets/job/13d/ct.csv") | ||
| let cn = load[<id: @vec {int -> int}, name: @vec {int -> string}, country_code: @vec {int -> string}, imdb_id: @vec {int -> string}, name_pcode_nf: @vec {int -> string}, name_pcode_sf: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/13d/cn.csv") | ||
|
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||
| let miidx_trie0 = sum(<i, _> <- range(miidx.size)) @phmap(miidx.size) { miidx.movie_id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| let interm0_trie0 = sum(<t_off, _> <- range(t.size)) | ||
| let x0 = t.id(t_off) in | ||
| if (x0 ∈ miidx_trie0) then | ||
| let miidx_trie1 = miidx_trie0(x0) in | ||
| sum(<miidx_off, _> <- miidx_trie1) | ||
| @phmap(promote[min_sum](1000000) + promote[min_sum](t.size)) { t.id(t_off) -> @smallvecdict(4) { <col1=t.title(t_off), col2=t.kind_id(t_off), col3=miidx.info(miidx_off), col4=miidx.info_type_id(miidx_off)> -> 1 } } | ||
| in | ||
|
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||
| let mc_trie0 = sum(<i, _> <- range(mc.size)) @phmap(mc.size) { mc.movie_id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| let kt_trie0 = sum(<i, _> <- range(kt.size)) @phmap(kt.size) { unique(kt.id(i)) -> 1 } in | ||
| let it2_trie0 = sum(<i, _> <- range(it2.size)) @phmap(it2.size) { unique(it2.id(i)) -> 1 } in | ||
| let it_trie0 = sum(<i, _> <- range(it.size)) @phmap(it.size) { unique(it.id(i)) -> 1 } in | ||
| let ct_trie0 = sum(<i, _> <- range(ct.size)) @phmap(ct.size) { unique(ct.id(i)) -> 1 } in | ||
| let cn_trie0 = sum(<i, _> <- range(cn.size)) @phmap(cn.size) { cn.id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| sum(<mi_off, _> <- range(mi.size)) | ||
| let x0 = mi.movie_id(mi_off) in | ||
| if (x0 ∈ interm0_trie0) then | ||
| if (x0 ∈ mc_trie0) then | ||
| let interm0_trie1 = interm0_trie0(x0) in | ||
| let mc_trie1 = mc_trie0(x0) in | ||
| sum(<interm0_tuple, _> <- interm0_trie1) | ||
| let x1 = interm0_tuple.col2 in | ||
| if (x1 ∈ kt_trie0) then | ||
| let kt_trie1 = kt_trie0(x1) in | ||
| let x2 = mi.info_type_id(mi_off) in | ||
| if (x2 ∈ it2_trie0) then | ||
| let it2_trie1 = it2_trie0(x2) in | ||
| let x3 = interm0_tuple.col4 in | ||
| if (x3 ∈ it_trie0) then | ||
| let it_trie1 = it_trie0(x3) in | ||
| sum(<mc_off, _> <- mc_trie1) | ||
| let x4 = mc.company_type_id(mc_off) in | ||
| if (x4 ∈ ct_trie0) then | ||
| let ct_trie1 = ct_trie0(x4) in | ||
| let x5 = mc.company_id(mc_off) in | ||
| if (x5 ∈ cn_trie0) then | ||
| let cn_trie1 = cn_trie0(x5) in | ||
| let mn_interm0 = <col1=interm0_tuple.col1, col3=interm0_tuple.col3> in | ||
| let mn_cn = sum(<cn_off, _> <- cn_trie1) promote[min_sum](<name=cn.name(cn_off)>) in | ||
| promote[min_sum](<col4=mn_interm0.col1, col5=mn_interm0.col3, col8=mn_cn.name>) | ||
|
|
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| @@ -0,0 +1,26 @@ | ||
| let mk = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, keyword_id: @vec {int -> int}, size: int>]("datasets/job/movie_keyword.csv") | ||
| let t = load[<id: @vec {int -> int}, title: @vec {int -> string}, imdb_index: @vec {int -> string}, kind_id: @vec {int -> int}, production_year: @vec {int -> int}, imdb_id: @vec {int -> string}, phonetic_code: @vec {int -> string}, episode_of_id: @vec {int -> int}, season_nr: @vec {int -> int}, episode_nr: @vec {int -> int}, series_years: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/title.csv") | ||
| let mc = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, company_id: @vec {int -> int}, company_type_id: @vec {int -> int}, note: @vec {int -> string}, size: int>]("datasets/job/movie_companies.csv") | ||
| let k = load[<id: @vec {int -> int}, keyword: @vec {int -> string}, phonetic_code: @vec {int -> string}, size: int>]("datasets/job/2c/k.csv") | ||
| let cn = load[<id: @vec {int -> int}, name: @vec {int -> string}, country_code: @vec {int -> string}, imdb_id: @vec {int -> string}, name_pcode_nf: @vec {int -> string}, name_pcode_sf: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/2c/cn.csv") | ||
|
|
||
| let k_trie0 = sum(<i, _> <- range(k.size)) @phmap(k.size) { unique(k.id(i)) -> 1 } in | ||
| let t_trie0 = sum(<i, _> <- range(t.size)) @phmap(t.size) { t.id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| let mc_trie0 = sum(<i, _> <- range(mc.size)) @phmap(mc.size) { mc.movie_id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| let cn_trie0 = sum(<i, _> <- range(cn.size)) @phmap(cn.size) { unique(cn.id(i)) -> 1 } in | ||
| sum(<mk_off, _> <- range(mk.size)) | ||
| let x0 = mk.keyword_id(mk_off) in | ||
| if (x0 ∈ k_trie0) then | ||
| let k_trie1 = k_trie0(x0) in | ||
| let x1 = mk.movie_id(mk_off) in | ||
| if (x1 ∈ t_trie0) then | ||
| if (x1 ∈ mc_trie0) then | ||
| let t_trie1 = t_trie0(x1) in | ||
| let mc_trie1 = mc_trie0(x1) in | ||
| sum(<mc_off, _> <- mc_trie1) | ||
| let x2 = mc.company_id(mc_off) in | ||
| if (x2 ∈ cn_trie0) then | ||
| let cn_trie1 = cn_trie0(x2) in | ||
| let mn_t = sum(<t_off, _> <- t_trie1) promote[min_sum](<title=t.title(t_off)>) in | ||
| promote[min_sum](<col2=mn_t.title>) | ||
|
|
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,38 @@ | ||
| let t1 = load[<id: @vec {int -> int}, title: @vec {int -> string}, imdb_index: @vec {int -> string}, kind_id: @vec {int -> int}, production_year: @vec {int -> int}, imdb_id: @vec {int -> string}, phonetic_code: @vec {int -> string}, episode_of_id: @vec {int -> int}, season_nr: @vec {int -> int}, episode_nr: @vec {int -> int}, series_years: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/title.csv") | ||
| let ml = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, linked_movie_id: @vec {int -> int}, link_type_id: @vec {int -> int}, size: int>]("datasets/job/movie_link.csv") | ||
| let t2 = load[<id: @vec {int -> int}, title: @vec {int -> string}, imdb_index: @vec {int -> string}, kind_id: @vec {int -> int}, production_year: @vec {int -> int}, imdb_id: @vec {int -> string}, phonetic_code: @vec {int -> string}, episode_of_id: @vec {int -> int}, season_nr: @vec {int -> int}, episode_nr: @vec {int -> int}, series_years: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/title.csv") | ||
| let mk = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, keyword_id: @vec {int -> int}, size: int>]("datasets/job/movie_keyword.csv") | ||
| let lt = load[<id: @vec {int -> int}, link: @vec {int -> string}, size: int>]("datasets/job/link_type.csv") | ||
| let k = load[<id: @vec {int -> int}, keyword: @vec {int -> string}, phonetic_code: @vec {int -> string}, size: int>]("datasets/job/32a/k.csv") | ||
|
|
||
| let ml_trie0 = sum(<i, _> <- range(ml.size)) @phmap(ml.size) { ml.movie_id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| let t2_trie0 = sum(<i, _> <- range(t2.size)) @phmap(t2.size) { t2.id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| let interm0_trie0 = sum(<t1_off, _> <- range(t1.size)) | ||
| let x0 = t1.id(t1_off) in | ||
| if (x0 ∈ ml_trie0) then | ||
| let ml_trie1 = ml_trie0(x0) in | ||
| sum(<ml_off, _> <- ml_trie1) | ||
| let x1 = ml.linked_movie_id(ml_off) in | ||
| if (x1 ∈ t2_trie0) then | ||
| let t2_trie1 = t2_trie0(x1) in | ||
| sum(<t2_off, _> <- t2_trie1) | ||
| @phmap(promote[min_sum](1000000) + promote[min_sum](t1.size)) { t1.id(t1_off) -> @smallvecdict(4) { <col1=t1.title(t1_off), col2=ml.linked_movie_id(ml_off), col3=ml.link_type_id(ml_off), col4=t2.title(t2_off)> -> 1 } } | ||
| in | ||
|
|
||
| let lt_trie0 = sum(<i, _> <- range(lt.size)) @phmap(lt.size) { lt.id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| let k_trie0 = sum(<i, _> <- range(k.size)) @phmap(k.size) { unique(k.id(i)) -> 1 } in | ||
| sum(<mk_off, _> <- range(mk.size)) | ||
| let x0 = mk.movie_id(mk_off) in | ||
| if (x0 ∈ interm0_trie0) then | ||
| let interm0_trie1 = interm0_trie0(x0) in | ||
| sum(<interm0_tuple, _> <- interm0_trie1) | ||
| let x1 = interm0_tuple.col3 in | ||
| if (x1 ∈ lt_trie0) then | ||
| let lt_trie1 = lt_trie0(x1) in | ||
| let x2 = mk.keyword_id(mk_off) in | ||
| if (x2 ∈ k_trie0) then | ||
| let k_trie1 = k_trie0(x2) in | ||
| let mn_interm0 = <col1=interm0_tuple.col1, col4=interm0_tuple.col4> in | ||
| let mn_lt = sum(<lt_off, _> <- lt_trie1) promote[min_sum](<link=lt.link(lt_off)>) in | ||
| promote[min_sum](<col3=mn_interm0.col1, col5=mn_interm0.col4, col6=mn_lt.link>) | ||
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| let mc = load[<id: @vec {int -> int}, movie_id: @vec {int -> int}, company_id: @vec {int -> int}, company_type_id: @vec {int -> int}, note: @vec {int -> string}, size: int>]("datasets/job/movie_companies.csv") | ||
| let t = load[<id: @vec {int -> int}, title: @vec {int -> string}, imdb_index: @vec {int -> string}, kind_id: @vec {int -> int}, production_year: @vec {int -> int}, imdb_id: @vec {int -> string}, phonetic_code: @vec {int -> string}, episode_of_id: @vec {int -> int}, season_nr: @vec {int -> int}, episode_nr: @vec {int -> int}, series_years: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/10b/t.csv") | ||
| let ct = load[<id: @vec {int -> int}, kind: @vec {int -> string}, size: int>]("datasets/job/company_type.csv") | ||
| let cn = load[<id: @vec {int -> int}, name: @vec {int -> string}, country_code: @vec {int -> string}, imdb_id: @vec {int -> string}, name_pcode_nf: @vec {int -> string}, name_pcode_sf: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/10b/cn.csv") | ||
| let ci = load[<id: @vec {int -> int}, person_id: @vec {int -> int}, movie_id: @vec {int -> int}, person_role_id: @vec {int -> int}, note: @vec {int -> string}, nr_order: @vec {int -> int}, role_id: @vec {int -> int}, size: int>]("datasets/job/10b/ci.csv") | ||
| let rt = load[<id: @vec {int -> int}, role: @vec {int -> string}, size: int>]("datasets/job/10b/rt.csv") | ||
| let chn = load[<id: @vec {int -> int}, name: @vec {int -> string}, imdb_index: @vec {int -> string}, imdb_id: @vec {int -> int}, name_pcode_cf: @vec {int -> string}, surname_pcode: @vec {int -> string}, md5sum: @vec {int -> string}, size: int>]("datasets/job/char_name.csv") | ||
|
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||
| let mc_trie0 = sum(<i, _> <- range(mc.size)) { mc.movie_id(i) -> { mc.company_type_id(i) -> { mc.company_id(i) -> @smallvecdict(0) { i -> 1 } } } } in | ||
| let t_trie0 = sum(<i, _> <- range(t.size)) @phmap(t.size) { t.id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| let ct_trie0 = sum(<i, _> <- range(ct.size)) { ct.id(i) -> 1 } in | ||
| let cn_trie0 = sum(<i, _> <- range(cn.size)) { cn.id(i) -> 1 } in | ||
| let interm0_trie0 = sum(<x0, mc_trie1> <- mc_trie0) | ||
| if (x0 ∈ t_trie0) then | ||
| let t_trie1 = t_trie0(x0) in | ||
| sum(<x1, mc_trie2> <- mc_trie1) | ||
| if (x1 ∈ ct_trie0) then | ||
| let ct_trie1 = ct_trie0(x1) in | ||
| sum(<x2, mc_trie3> <- mc_trie2) | ||
| if (x2 ∈ cn_trie0) then | ||
| let cn_trie1 = cn_trie0(x2) in | ||
| sum(<mc_off, _> <- mc_trie3) | ||
| sum(<t_off, _> <- t_trie1) | ||
| { mc.movie_id(mc_off) -> @smallvecdict(0) { <col0=mc.movie_id(mc_off), col1=mc.company_type_id(mc_off), col2=mc.company_id(mc_off), col3=t.title(t_off)> -> 1 } } | ||
| in | ||
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||
| let ci_trie0 = sum(<i, _> <- range(ci.size)) { ci.role_id(i) -> { ci.movie_id(i) -> { ci.person_role_id(i) -> 1 } } } in | ||
| let rt_trie0 = sum(<i, _> <- range(rt.size)) { rt.id(i) -> 1 } in | ||
| let chn_trie0 = sum(<i, _> <- range(chn.size)) @phmap(chn.size) { chn.id(i) -> @smallvecdict(4) { i -> 1 } } in | ||
| sum(<x0, ci_trie1> <- ci_trie0) | ||
| if (x0 ∈ rt_trie0) then | ||
| let rt_trie1 = rt_trie0(x0) in | ||
| sum(<x1, ci_trie2> <- ci_trie1) | ||
| if (x1 ∈ interm0_trie0) then | ||
| let interm0_trie1 = interm0_trie0(x1) in | ||
| sum(<x2, ci_trie3> <- ci_trie2) | ||
| if (x2 ∈ chn_trie0) then | ||
| let chn_trie1 = chn_trie0(x2) in | ||
| let mn_interm0 = sum(<interm0_tuple, _> <- interm0_trie1) promote[min_sum](<col3=interm0_tuple.col3>) in | ||
| let mn_chn = sum(<chn_off, _> <- chn_trie1) promote[min_sum](<name=chn.name(chn_off)>) in | ||
| promote[min_sum](<col5=mn_interm0.col3, col6=mn_chn.name>) | ||
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