From 22d0ce14dbee800f6905ac3589aa3af800bfbe66 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E5=BC=A0=E5=BD=A6=E9=92=8A?= <zhangyanzhao@igengmei.com>
Date: Mon, 29 Apr 2019 16:04:16 +0800
Subject: [PATCH] =?UTF-8?q?=E6=8A=8A=E6=9C=80=E8=BF=91=E4=B8=80=E5=A4=A9?=
=?UTF-8?q?=E7=9A=84=E6=95=B0=E6=8D=AE=E9=9B=86=E6=94=BE=E8=BF=9B=E8=AE=AD?=
=?UTF-8?q?=E7=BB=83=E9=9B=86?=
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---
tensnsorflow/multi.py | 15 +++++++++------
1 file changed, 9 insertions(+), 6 deletions(-)
diff --git a/tensnsorflow/multi.py b/tensnsorflow/multi.py
index a279d3ad..dc35a39f 100644
--- a/tensnsorflow/multi.py
+++ b/tensnsorflow/multi.py
@@ -141,10 +141,13 @@ def get_predict(date,value_map,app_list_map,level2_map,level3_map):
"recover_time","top") \
.rdd.map(lambda x: (app_list_func(x[0], app_list_map), app_list_func(x[1], level2_map),
app_list_func(x[2], level3_map), x[3],x[4],x[5],x[6],x[7],x[8],
- value_map[x[3]], value_map[x[9]],
- value_map[x[10]], value_map[x[11]], value_map[x[12]], value_map[x[13]],
- value_map[x[14]], value_map[x[15]], value_map[x[16]], value_map[x[17]],
- value_map[x[18]], value_map[x[19]], value_map[x[20]], value_map.get(x[21],30000),
+ value_map.get(x[3], 300000),value_map.get(x[9], 299999),
+ value_map.get(x[10], 299998), value_map.get(x[11], 299997),
+ value_map.get(x[12], 299996), value_map.get(x[13], 299995),
+ value_map.get(x[14], 299994),value_map.get(x[15], 299993),
+ value_map.get(x[16], 299992),value_map.get(x[17], 299991),
+ value_map.get(x[18], 299990),value_map.get(x[19], 299989),
+ value_map.get(x[20], 299988),value_map.get(x[21], 299987),
value_map[date]))
rdd.persist()
@@ -173,9 +176,9 @@ def get_predict(date,value_map,app_list_map,level2_map,level3_map):
.map(lambda x: (x[0], x[1], x[2], x[9], x[10], x[11], x[12], x[13], x[14], x[15],
x[16, x[17], x[18], x[19], x[20], x[21], x[22], x[23]]))) \
.toDF("app_list", "level2_ids", "level3_ids", "ucity_id",
- "ccity_name", "device_type", "manufacturer", "channel", "top", "time", "hospital_id",
+ "ccity_name", "device_type", "manufacturer", "channel", "time", "hospital_id",
"treatment_method", "price_min", "price_max", "treatment_time", "maintain_time",
- "recover_time","stat_date").write.csv('/recommend/nearby', mode='overwrite', header=True)
+ "recover_time","top","stat_date").write.csv('/recommend/nearby', mode='overwrite', header=True)
rdd.unpersist()
--
2.18.0