apply_oracle_lab10.txt - SQL> SQL> SQL> Step#1 SQL> SQL> Using the query from Lab 7 Step 4 insert the 135 SQL> rows in the PRICE table created in Lab 6

apply_oracle_lab10.txt - SQL> SQL> SQL> Step#1 SQL> SQL>...

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Unformatted text preview: SQL> SQL> -- -------------------------------------------------------- SQL> -- Step #1 SQL> -- ------- SQL> -- Using the query from Lab 7, Step 4, insert the 135 SQL> -- rows in the PRICE table created in Lab 6. SQL> -- -------------------------------------------------------- SQL> SELECT DISTINCT c.contact_id 2 FROM member m INNER JOIN transaction_upload tu 3 ON m.account_number = tu.account_number INNER JOIN contact c 4 ON m.member_id = c.member_id 5 WHERE c.first_name = tu.first_name 6 AND NVL(c.middle_name,'x') = NVL(tu.middle_name,'x') 7 AND c.last_name = tu.last_name 8 ORDER BY c.contact_id; CONTACT_ID ---------- 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 15 rows selected. SQL> SQL> ---Query--- SQL> SELECT COUNT(*) AS "Rental before count" 2 FROM rental; Rental before count ------------------- 8 1 row selected. SQL> ----------------------------------------------------------- SQL> SET NULL '<Null>' SQL> COLUMN rental_id FORMAT 9999 HEADING "Rental|ID #" SQL> COLUMN customer FORMAT 9999 HEADING "Customer|ID #" SQL> COLUMN check_out_date FORMAT A9 HEADING "Check Out|Date" SQL> COLUMN return_date FORMAT A10 HEADING "Return|Date" SQL> COLUMN created_by FORMAT 9999 HEADING "Created|By" SQL> COLUMN creation_date FORMAT A10 HEADING "Creation|Date" SQL> COLUMN last_updated_by FORMAT 9999 HEADING "Last|Update|By" SQL> COLUMN last_update_date FORMAT A10 HEADING "Last|Updated" SQL> insert into rental 2 ( rental_id 3 ,customer_id 4 ,check_out_date 5 ,return_date 6 ,created_by 7 ,creation_date 8 ,last_updated_by 9 ,last_update_date) 10 SELECT NVL(tmp1.rental_id,rental_s1.NEXTVAL) AS rental_id 11 , tmp1.contact_id AS contact_id 12 , tmp1.check_out_date AS check_out_date 13 , tmp1.return_date AS return_date 14 , 1 AS created_by 15 , TRUNC(SYSDATE) AS creation_date 16 , 1 AS last_updated_by 17 , TRUNC(SYSDATE) AS last_update_date 18 From (select DISTINCT 19 r.rental_id 20 ,c.contact_id as contact_id 21 ,tu.check_out_date as check_out_date 22 ,tu.return_date as return_date 23 , 1 24 ,sysdate 25 ,1 26 ,sysdate 27 From member m inner join contact c 28 On m.member_id = c.member_id 29 INNER JOIN transaction_upload tu 30 ON tu.account_number = m.account_number 31 and tu.first_name = c.first_name 32 and NVL(tu.middle_name, 'x') = NVL(c.middle_name, 'x') 33 and tu.last_name = c.last_name 34 and tu.account_number = m.account_number 35 Left join rental r 36 on c.contact_id = r.customer_id 37 and TRUNC(tu.check_out_date) = TRUNC(r.check_out_date) 38 and TRUNC(tu.return_date) = TRUNC(r.return_date)) TMP1; 4681 rows created. SQL> SQL> ---Query--- SQL> COL rental_count FORMAT 999,999 HEADING "Rental|after|Count" SQL> SELECT COUNT(*) AS rental_count 2 FROM rental; Rental after Count -------- 4,689 1 row selected. SQL> -- -------------------------------------------------------- SQL> -- Step #2 SQL> -- ------- SQL> -- Add a NOT NULL constraint on the PRICE_TYPE column SQL> -- of the PRICE table. SQL> -- -------------------------------------------------------- SQL> ---Query--- SQL> SELECT COUNT(*) AS "Rental Item Before Count" 2 FROM rental_item; Rental Item Before Count ------------------------ 13 1 row selected. SQL> ----------------------------------------------------------- SQL> insert into rental_item 2 ( rental_item_id 3 , rental_id 4 , item_id 5 , rental_item_price 6 , rental_item_type 7 , created_by 8 , creation_date 9 , last_updated_by 10 , last_update_date) 11 SQL> (SELECT NVL(ri.rental_item_id,rental_item_s1.NEXTVAL) 2 , r.rental_id 3 , tu.item_id 4 , 1 AS created_by 5 , TRUNC(SYSDATE) AS creation_date 6 , 1 AS last_updated_by 7 , TRUNC(SYSDATE) AS last_update_date 8 , cl.common_lookup_id AS rental_item_type 9 , r.return_date - r.check_out_date AS rental_item_price 10 FROM member m inner join contact c 11 On m.member_id = c.member_id 12 INNER JOIN transaction_upload tu 13 ON tu.account_number = m.account_number 14 and tu.first_name = c.first_name 15 and NVL(tu.middle_name, 'x') = NVL(c.middle_name, 'x') 16 and tu.last_name = c.last_name 17 Left join rental r 18 on c.contact_id = r.customer_id 19 and TRUNC(tu.check_out_date) = TRUNC(r.check_out_date) 20 and TRUNC(tu.return_date) = TRUNC(r.return_date) 21 inner join common_lookup cl 22 on cl.common_lookup_table = 'RENTAL_ITEM' 23 and cl.common_lookup_column = 'RENTAL_ITEM_TYPE' 24 and cl.common_lookup_type = tu.rental_item_type 25 left join rental_item ri 26 on r.rental_id = ri.rental_id); Rental ITEM Created Creation NVL(RI.RENTAL_ITEM_ID,RENTAL_ITEM_S1.NEXTVAL) ID # ID By Date --------------------------------------------- ------ ----- ------- ---------- Last Rental Rental Update Last Item Item By Updated Type Price ------ ---------- ---------- ------- 1014 5002 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1015 5002 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1016 4596 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1017 4596 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1018 4596 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1019 1198 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1020 1198 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1021 1198 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1022 2180 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1023 3271 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1024 3271 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1025 3271 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1026 3271 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1027 3271 1007 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1028 5306 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1029 1585 1007 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1030 1585 1007 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1031 1585 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1032 3656 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1033 2886 1019 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1034 2886 1019 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1035 5062 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1036 5062 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1037 5062 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1038 5062 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1039 2974 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1040 2974 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1041 2974 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1042 2116 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1043 2116 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1044 1366 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1045 2790 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1046 2790 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1047 2790 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1048 2508 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1049 1243 1008 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1050 4036 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1051 4036 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1052 4036 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1053 4876 1001 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1054 4876 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1055 4876 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1056 1057 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1057 1057 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1058 1057 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1059 1057 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1060 3598 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1061 3598 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1062 3598 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1063 3598 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1064 3598 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1065 3598 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1066 3598 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1067 1915 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1068 5339 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1069 5339 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1070 5339 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1071 3633 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1072 1946 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1073 1946 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1074 1946 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1075 1946 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1076 2895 1008 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1077 1450 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1078 2684 1011 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1079 2684 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1080 2684 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1081 2684 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1082 2298 1008 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1083 4152 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1084 4152 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1085 2081 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1086 1556 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1087 1556 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1088 1556 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1089 1556 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1090 5674 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1091 5674 1001 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1092 5674 1001 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1093 5674 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1094 5434 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1095 5434 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1096 5434 1008 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1097 3565 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1098 3565 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1099 3565 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1100 3565 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1101 1333 1008 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1102 1333 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1103 5479 1007 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1104 5479 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1105 5608 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1106 5608 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1107 5608 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1108 2488 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1109 2488 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1110 3422 1008 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1111 5122 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1112 5122 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1113 5122 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1114 5122 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1115 4186 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1116 2858 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1117 2858 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1118 2858 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1119 2858 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1120 2858 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1121 3261 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1122 3261 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1123 3431 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1124 1129 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1125 1129 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1126 1129 1011 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1127 1129 1011 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1128 1129 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1129 1129 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1130 1129 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1131 1129 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1132 1129 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1133 2056 1017 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1134 1253 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1135 1253 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1136 1107 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1137 4998 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1138 4998 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1139 4998 1001 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1140 4998 1007 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1141 4998 1007 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1142 4381 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1143 4381 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1144 4381 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1145 1776 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1146 1776 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1147 2809 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1148 2809 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1149 2809 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1150 2809 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1151 2809 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1152 1543 1008 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1153 1543 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1154 1543 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1155 1543 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1156 1543 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1157 4082 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1158 4082 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1159 4082 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1160 4105 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1161 3979 1019 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1162 3979 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1163 3979 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1164 5244 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1165 5244 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1166 1878 1006 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1167 1878 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1168 1878 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1169 2375 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1170 1948 1019 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1171 1948 1006 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1172 1948 1011 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1173 1948 1011 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1174 4062 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1175 4062 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1176 4062 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1177 2043 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1178 2043 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1179 3134 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1180 3134 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1181 3134 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1182 3134 1007 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1183 4860 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1184 4860 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1185 4250 1002 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1186 4250 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1187 4250 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1188 4250 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1189 3781 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1190 3781 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1191 4122 1017 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1192 2265 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1193 2265 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1194 2265 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1195 2485 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1196 4826 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1197 1718 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1198 1718 1001 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1199 3436 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1200 3436 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1201 3436 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1202 3800 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1203 3161 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1204 3161 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1205 3965 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1206 3965 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1207 3965 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1208 3965 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1209 3198 1006 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1210 3198 1001 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1211 1589 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1212 1589 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1213 1589 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1214 3738 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1215 3738 1006 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1216 3738 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1217 3738 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1218 3498 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1219 2245 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1220 2245 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1221 5209 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1222 5209 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1223 5209 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1224 5209 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1225 2743 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1226 2743 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1227 2743 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1228 3306 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1229 3306 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1230 3306 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1231 3306 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1232 4889 1001 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1233 4287 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1234 3946 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1235 1211 1006 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1236 1211 1011 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1237 1211 1017 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1238 2781 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1239 2781 1002 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1240 2781 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1241 2781 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1242 5157 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1243 4177 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1244 4768 1019 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1245 2496 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1246 1131 1011 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1247 1131 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1248 3529 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1249 3529 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1250 1942 1015 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1251 1942 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1252 4811 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1253 4601 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1254 4601 1016 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1255 1123 1005 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1256 1110 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1257 4340 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1258 4340 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1259 3351 1007 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1260 2349 1001 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1261 3952 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1262 2383 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1263 2383 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1264 4304 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1265 4304 1009 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1266 2697 1004 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1267 5545 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1268 5545 1018 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1269 5545 1002 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1270 5545 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1271 5545 1007 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1272 2391 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1273 2391 1003 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1274 2391 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1275 2391 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1276 2810 1011 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1277 2739 1019 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1278 1258 1008 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1279 1258 1008 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1280 3826 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1281 3826 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1282 3826 1010 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1283 1528 1007 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1284 3646 1013 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1285 2516 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1286 2516 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1287 2516 1020 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1288 2516 1014 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1289 5090 1007 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1290 5090 1012 1 17-MAR-19 1 17-MAR-19 ########## 3.00 1291 5090 1012 1 17-MAR-19 1 17-MAR-19 ########## 3...
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  • Winter '17

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