1 files changed, 0 insertions, 101 deletions
diff --git a/sample-apps/blog-recommendation/src/pig/feed_content_and_tensor_vespa.pig b/sample-apps/blog-recommendation/src/pig/feed_content_and_tensor_vespa.pig
deleted file mode 100644
index 70d14dc1cc1..00000000000
--- a/sample-apps/blog-recommendation/src/pig/feed_content_and_tensor_vespa.pig
+++ /dev/null
@@ -1,101 +0,0 @@
--- Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-REGISTER vespa-hadoop.jar
-
--- Create valid Vespa put operations
-DEFINE VespaPutOperationDoc
-       com.yahoo.vespa.hadoop.pig.VespaDocumentOperation(
-            'operation=put',
-            'docid=id:blog-recommendation:blog_post::<post_id>',
-            'create-tensor-fields=user_item_cf',
-            'simple-array-fields=tags,categories'
-       );
-
-DEFINE VespaPutOperationUser
-       com.yahoo.vespa.hadoop.pig.VespaDocumentOperation(
-            'operation=put',
-            'docid=id:blog-recommendation:user::<user_id>',
-            'create-tensor-fields=user_item_cf',
-            'simple-array-fields=has_read_items'
-       );
-
--- Transform tabular data to a Vespa document operation JSON format
-DEFINE VespaStorage
-       com.yahoo.vespa.hadoop.pig.VespaStorage();
-
--- DEFINE VespaStorage
---        com.yahoo.vespa.hadoop.pig.VespaStorage(
---             'create-document-operation=true',
---             'operation=put',
---             'docid=id:blog-recommendation:blog_post::<post_id>'
---        );
-
--- Load data from any source - here we load using PigStorage
-data = LOAD 'blog-recommendation/trainPostsFinal' USING JsonLoader('date_gmt:chararray, language:chararray, author:chararray, url:chararray, title:chararray, blog:chararray, post_id:chararray, tags:{T:(tag_name:chararray)}, blogname:chararray, date:chararray, content:chararray, categories:{T:(category_name:chararray)}, likes:{T:(dt:chararray, uid:chararray)}');
-
-data_for_feed = FOREACH data GENERATE 
-  date_gmt, 
-  language, 
-  author, 
-  url, 
-  title, 
-  blog, 
-  post_id, 
-  tags, 
-  blogname,
-  content, 
-  categories;
-
-data_doc = LOAD 'blog-recommendation/user_item_cf/product_features' USING JsonLoader('post_id:chararray, user_item_cf:[double]');
-
-data_content_and_doc_tensor = JOIN data_for_feed BY post_id LEFT, data_doc BY post_id;
-data_content_and_doc_tensor = FOREACH data_content_and_doc_tensor GENERATE
-  date_gmt AS date_gmt, 
-  language AS language, 
-  author AS author, 
-  url AS url, 
-  title AS title, 
-  blog AS blog, 
-  data_for_feed::post_id as post_id, 
-  tags AS tags, 
-  blogname AS blogname,
-  content AS content, 
-  categories AS categories,
-  user_item_cf AS user_item_cf,
-  (user_item_cf IS NOT NULL ? 1 : 0) AS has_user_item_cf;
-
-data_content_and_doc_tensor_feed = FOREACH data_content_and_doc_tensor GENERATE VespaPutOperationDoc(*);
-
--- use cf latent factor
-data_user = LOAD 'blog-recommendation/user_item_cf/user_features' USING JsonLoader('user_id:chararray, user_item_cf:[double]');
-data_user = FOREACH data_user GENERATE  
-  user_id AS user_id,
-  user_item_cf AS user_item_cf;
-  
-
--- Articles already liked
-data_likes = FOREACH data GENERATE post_id, FLATTEN(likes) AS (dt, uid); 
-
-post_liked_per_user = GROUP data_likes BY uid;
-post_liked_per_user = FOREACH post_liked_per_user GENERATE group AS user_id, data_likes.post_id AS has_read_items;
-
--- Join user data
-data_user = JOIN post_liked_per_user BY user_id FULL, data_user BY user_id;
-
-data_user = FOREACH data_user GENERATE (post_liked_per_user::user_id IS NOT NULL ? post_liked_per_user::user_id : data_user::user_id) AS user_id,
-                                       user_item_cf AS user_item_cf,
-                                       (user_item_cf IS NOT NULL ? 1 : 0) AS has_user_item_cf,
-                                       has_read_items AS has_read_items;
-data_user = FILTER data_user BY user_id IS NOT NULL;
-
-data_user_for_feed = FOREACH data_user GENERATE VespaPutOperationUser(*);
-
-joint_content_tensors = UNION data_content_and_doc_tensor_feed, data_user_for_feed;
-
--- STORE data_for_feed into 'vespa_put_operation';
-
--- Store into Vespa
-STORE joint_content_tensors INTO '$ENDPOINT' USING VespaStorage();
-
-
-
-