I have a dynamic field named *_value. The field os_value which contains value like android 5,android 5.1, android 6 etc.
While doing facet on field os_value, the values are getting tokenized to android count as 3 , 5 as 1 , 5.1 as 1 and 6 as 1.
The mapping for the index is as below.
{
"test_prod": {
"aliases": {},
"mappings": {
"products": {
"properties": {
"*_capacity": {
"type": "string",
"index": "not_analyzed"
},
"*_value": {
"type": "string",
"index": "not_analyzed",
"include_in_all": false
},
"*_rating": {
"type": "double"
},
"*_value": {
"type": "string",
"index": "not_analyzed"
},
"attribute_set": {
"type": "string",
"index": "not_analyzed"
},
"availability": {
"type": "integer"
},
"battery_capacity": {
"type": "string"
},
"battery_capacity_value": {
"type": "long"
},
"battery_life_rating": {
"type": "long"
},
"brand": {
"type": "string",
"index": "not_analyzed"
},
"brand_label": {
"type": "string"
},
"camera_rating": {
"type": "long"
},
"capacity": {
"type": "long"
},
"category": {
"type": "string",
"index": "not_analyzed"
},
"class": {
"type": "string",
"index": "not_analyzed"
},
"color": {
"type": "string",
"index": "not_analyzed"
},
"configuration": {
"type": "string",
"index": "not_analyzed"
},
"connectivity": {
"type": "string",
"index": "not_analyzed"
},
"created_at": {
"type": "integer"
},
"description": {
"type": "string"
},
"design_rating": {
"type": "long"
},
"designed_for": {
"type": "string",
"index": "not_analyzed"
},
"discount": {
"type": "double"
},
"display_rating": {
"type": "long"
},
"features": {
"type": "string",
"index": "not_analyzed"
},
"front_camera_resolution_range": {
"type": "string",
"index": "not_analyzed"
},
"front_camera_resolution_value": {
"type": "long"
},
"graphics_memory_capacity": {
"type": "string"
},
"hard_disk_capacity": {
"type": "string"
},
"headset_design": {
"type": "string",
"index": "not_analyzed"
},
"headset_type": {
"type": "string",
"index": "not_analyzed"
},
"id": {
"type": "integer"
},
"image_big": {
"type": "string",
"index": "not_analyzed",
"include_in_all": false
},
"image_slider": {
"type": "string",
"index": "not_analyzed",
"include_in_all": false
},
"image_thumb": {
"type": "string",
"index": "not_analyzed",
"include_in_all": false
},
"interface": {
"type": "string",
"index": "not_analyzed"
},
"internal_storage": {
"type": "string",
"index": "not_analyzed"
},
"is_default": {
"type": "integer"
},
"is_exclusive": {
"type": "integer"
},
"key": {
"type": "string"
},
"last_update": {
"type": "date",
"format": "Y-m-d H:m:s"
},
"material": {
"type": "string"
},
"model": {
"type": "string"
},
"mrp": {
"type": "double"
},
"ndtv_rating": {
"type": "long"
},
"network_type": {
"type": "string",
"index": "not_analyzed"
},
"os": {
"type": "string",
"index": "not_analyzed"
},
"os_label": {
"type": "string"
},
"performance_rating": {
"type": "long"
},
"popularity": {
"type": "integer"
},
"processor_core": {
"type": "string",
"index": "not_analyzed"
},
"processor_name": {
"type": "string",
"index": "not_analyzed"
},
"product_id": {
"type": "long"
},
"product_specs": {
"type": "string"
},
"promo_label": {
"type": "string"
},
"pros_cons": {
"type": "string"
},
"ram_range": {
"type": "string"
},
"ram_value": {
"type": "long"
},
"rear_camera_resolution_range": {
"type": "string",
"index": "not_analyzed"
},
"rear_camera_resolution_value": {
"type": "long"
},
"register_mode": {
"type": "string"
},
"related_sku": {
"type": "string"
},
"release_priority": {
"type": "long"
},
"review_url": {
"type": "string"
},
"screen_size": {
"type": "string",
"index": "not_analyzed"
},
"screen_size_value": {
"type": "double"
},
"selling_price": {
"type": "double"
},
"shop_url": {
"type": "string"
},
"sim3g": {
"type": "long"
},
"sim4g": {
"type": "long"
},
"sim_type": {
"type": "string"
},
"sku": {
"type": "string"
},
"slug": {
"type": "string"
},
"software_rating": {
"type": "long"
},
"source": {
"type": "string"
},
"ssd_capacity": {
"type": "string"
},
"stock": {
"type": "string"
},
"subtitle": {
"type": "string"
},
"system_memory": {
"type": "string"
},
"tags": {
"type": "string"
},
"theme": {
"type": "string",
"index": "not_analyzed"
},
"title": {
"type": "string"
},
"title_raw": {
"type": "string",
"index": "not_analyzed"
},
"title_suggest": {
"type": "string",
"analyzer": "autocomplete_analyzer",
"search_analyzer": "standard"
},
"type": {
"type": "string",
"index": "not_analyzed"
},
"value_for_money_rating": {
"type": "long"
},
"variant_id": {
"type": "integer"
},
"voice_calling": {
"type": "integer"
},
"wifi": {
"type": "integer"
},
"wired_or_wireless": {
"type": "string",
"index": "not_analyzed"
}
}
}
},
"settings": {
"index": {
"creation_date": "1467010796904",
"analysis": {
"filter": {
"autocomplete_filter": {
"type": "edge_ngram",
"min_gram": "1",
"max_gram": "20"
}
},
"analyzer": {
"autocomplete_analyzer": {
"filter": ["lowercase", "autocomplete_filter"],
"type": "custom",
"tokenizer": "standard"
}
}
},
"number_of_shards": "5",
"number_of_replicas": "1",
"uuid": "BJbw5tD-assad",
"version": {
"created": "2030399"
}
}
},
"warmers": {}
}
}
Also the values are converting to lowercase while faceting . Am I doing anything wrong? . Please help.
Ok, I see what you're trying to achieve. What you actually need are dynamic templates. You'll need to delete your index and recreate it like this:
POST test_prod
{
"mappings": {
"products": {
"dynamic_templates": [
{
"capacities": {
"match_mapping_type": "string",
"match": "*_capacity",
"mapping": {
"type": "string",
"index": "not_analyzed"
}
}
},
{
"values": {
"match_mapping_type": "string",
"match": "*_value",
"mapping": {
"type": "string",
"index": "not_analyzed"
}
}
},
{
"ratings": {
"match": "*_rating",
"mapping": {
"type": "double"
}
}
}
],
"properties": {
"attribute_set": {
"type": "string",
"index": "not_analyzed"
},
"availability": {
"type": "integer"
},
"battery_capacity": {
"type": "string"
},
"battery_capacity_value": {
"type": "long"
},
"battery_life_rating": {
"type": "long"
},
"brand": {
"type": "string",
"index": "not_analyzed"
},
"brand_label": {
"type": "string"
},
"camera_rating": {
"type": "long"
},
"capacity": {
"type": "long"
},
"category": {
"type": "string",
"index": "not_analyzed"
},
"class": {
"type": "string",
"index": "not_analyzed"
},
"color": {
"type": "string",
"index": "not_analyzed"
},
"configuration": {
"type": "string",
"index": "not_analyzed"
},
"connectivity": {
"type": "string",
"index": "not_analyzed"
},
"created_at": {
"type": "integer"
},
"description": {
"type": "string"
},
"design_rating": {
"type": "long"
},
"designed_for": {
"type": "string",
"index": "not_analyzed"
},
"discount": {
"type": "double"
},
"display_rating": {
"type": "long"
},
"features": {
"type": "string",
"index": "not_analyzed"
},
"front_camera_resolution_range": {
"type": "string",
"index": "not_analyzed"
},
"front_camera_resolution_value": {
"type": "long"
},
"graphics_memory_capacity": {
"type": "string"
},
"hard_disk_capacity": {
"type": "string"
},
"headset_design": {
"type": "string",
"index": "not_analyzed"
},
"headset_type": {
"type": "string",
"index": "not_analyzed"
},
"id": {
"type": "integer"
},
"image_big": {
"type": "string",
"index": "not_analyzed",
"include_in_all": false
},
"image_slider": {
"type": "string",
"index": "not_analyzed",
"include_in_all": false
},
"image_thumb": {
"type": "string",
"index": "not_analyzed",
"include_in_all": false
},
"interface": {
"type": "string",
"index": "not_analyzed"
},
"internal_storage": {
"type": "string",
"index": "not_analyzed"
},
"is_default": {
"type": "integer"
},
"is_exclusive": {
"type": "integer"
},
"key": {
"type": "string"
},
"last_update": {
"type": "date",
"format": "Y-m-d H:m:s"
},
"material": {
"type": "string"
},
"model": {
"type": "string"
},
"mrp": {
"type": "double"
},
"ndtv_rating": {
"type": "long"
},
"network_type": {
"type": "string",
"index": "not_analyzed"
},
"os": {
"type": "string",
"index": "not_analyzed"
},
"os_label": {
"type": "string"
},
"performance_rating": {
"type": "long"
},
"popularity": {
"type": "integer"
},
"processor_core": {
"type": "string",
"index": "not_analyzed"
},
"processor_name": {
"type": "string",
"index": "not_analyzed"
},
"product_id": {
"type": "long"
},
"product_specs": {
"type": "string"
},
"promo_label": {
"type": "string"
},
"pros_cons": {
"type": "string"
},
"ram_range": {
"type": "string"
},
"ram_value": {
"type": "long"
},
"rear_camera_resolution_range": {
"type": "string",
"index": "not_analyzed"
},
"rear_camera_resolution_value": {
"type": "long"
},
"register_mode": {
"type": "string"
},
"related_sku": {
"type": "string"
},
"release_priority": {
"type": "long"
},
"review_url": {
"type": "string"
},
"screen_size": {
"type": "string",
"index": "not_analyzed"
},
"screen_size_value": {
"type": "double"
},
"selling_price": {
"type": "double"
},
"shop_url": {
"type": "string"
},
"sim3g": {
"type": "long"
},
"sim4g": {
"type": "long"
},
"sim_type": {
"type": "string"
},
"sku": {
"type": "string"
},
"slug": {
"type": "string"
},
"software_rating": {
"type": "long"
},
"source": {
"type": "string"
},
"ssd_capacity": {
"type": "string"
},
"stock": {
"type": "string"
},
"subtitle": {
"type": "string"
},
"system_memory": {
"type": "string"
},
"tags": {
"type": "string"
},
"theme": {
"type": "string",
"index": "not_analyzed"
},
"title": {
"type": "string"
},
"title_raw": {
"type": "string",
"index": "not_analyzed"
},
"title_suggest": {
"type": "string",
"analyzer": "autocomplete_analyzer",
"search_analyzer": "standard"
},
"type": {
"type": "string",
"index": "not_analyzed"
},
"value_for_money_rating": {
"type": "long"
},
"variant_id": {
"type": "integer"
},
"voice_calling": {
"type": "integer"
},
"wifi": {
"type": "integer"
},
"wired_or_wireless": {
"type": "string",
"index": "not_analyzed"
}
}
}
},
"settings": {
"index": {
"analysis": {
"filter": {
"autocomplete_filter": {
"type": "edge_ngram",
"min_gram": "1",
"max_gram": "20"
}
},
"analyzer": {
"autocomplete_analyzer": {
"filter": [
"lowercase",
"autocomplete_filter"
],
"type": "custom",
"tokenizer": "standard"
}
}
},
"number_of_shards": "5",
"number_of_replicas": "1"
}
}
}
Related
I've been trying to build an index in ES and add the initial items to it (around 350k), using PHP.
I tried all kinds of batch sizes (from 10 items to 1k), check the count, check the threshold, but for some reason it doesn't index every item.
It just skips over some random items, without any errors in the batch result response. I feel like I tried everything and I have to idea what to do next
I'm using Amazon OpenSearch with the latest supported ES (7.10).
The index looks like this:
{
"wonder-search": {
"aliases": {},
"mappings": {
"properties": {
"address": {
"type": "text"
},
"city": {
"type": "text"
},
"city_id": {
"type": "integer"
},
"duration": {
"type": "integer"
},
"filename": {
"type": "text"
},
"geo_point": {
"type": "geo_point"
},
"icon": {
"type": "keyword"
},
"is_sandbox": {
"type": "integer"
},
"item_id": {
"type": "integer"
},
"item_label": {
"type": "keyword"
},
"latitude": {
"type": "float"
},
"longitude": {
"type": "float"
},
"search_text_caption_json": {
"type": "text",
"index_phrases": true
},
"search_text_city_json": {
"type": "text",
"index_phrases": true
},
"search_text_completion": {
"type": "completion",
"analyzer": "simple",
"preserve_separators": true,
"preserve_position_increments": true,
"max_input_length": 50,
"contexts": [
{
"name": "type",
"type": "CATEGORY"
}
]
},
"search_text_country_json": {
"type": "text",
"index_phrases": true
},
"search_text_cuisine_name_json": {
"type": "text",
"index_phrases": true
},
"search_text_location_name_json": {
"type": "text",
"index_phrases": true
},
"search_text_state_json": {
"type": "text",
"index_phrases": true
},
"search_text_tag_name_json": {
"type": "text",
"index_phrases": true
},
"search_text_username_json": {
"type": "text",
"index_phrases": true
},
"sort": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"sort_score": {
"type": "double"
},
"type": {
"type": "text"
},
"user_icon": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"user_id": {
"type": "integer"
},
"username": {
"type": "keyword"
},
"vanity_url": {
"type": "keyword"
},
"video_count": {
"type": "integer"
}
}
},
"settings": {
"index": {
"routing": {
"allocation": {
"include": {
"_tier_preference": "data_content"
}
}
},
"mapping": {
"ignore_malformed": "true"
},
"number_of_shards": "1",
"provided_name": "wonder-search",
"creation_date": "1671003076106",
"number_of_replicas": "1",
"uuid": "YQh1q40WTneLE4MWDWhArw",
"version": {
"created": "7100199"
}
}
}
}
}
and one item looks like this:
{
"_index": "wonder-search",
"_type": "_doc",
"_id": "wq2LD4UBUAuy7FQPhtZh",
"_version": 1,
"_seq_no": 2003,
"_primary_term": 1,
"found": true,
"_source": {
"sort": "4004",
"item_id": "4934",
"user_id": "434",
"user_icon": "/site-content/avatars/Sp8AXjTJvMbRao2oZbuiUuSVH042-1597776099045.jpeg",
"username": "chuurros",
"item_label": "Kyoto Katsugyu【京都勝牛】",
"search_text_username_json": [
"chuurros"
],
"search_text_caption_json": [
"Absolutely love their gyukatsu (beef katsu) here! Delicious and will keep you wanting more! 🥰"
],
"search_text_city_json": [
"Toronto"
],
"search_text_state_json": [
"Ontario"
],
"search_text_country_json": [
"Canada"
],
"search_text_location_name_json": [
"Kyoto Katsugyu【京都勝牛】"
],
"search_text_tag_name_json": [
"japanese",
"restaurant",
"asian",
"dining",
"topcollection-4934"
],
"search_text_cuisine_name_json": [],
"type": "video",
"vanity_url": "",
"icon": "",
"city": "Toronto",
"city_id": "439",
"latitude": "43.65682410",
"longitude": "-79.37617410",
"address": "134 Dundas St E",
"duration": "9.57",
"video_count": "0",
"sort_score": "43",
"filename": "373d75fd-4292-4e5b-a239-4b1c39ffc86c.MOV",
"is_sandbox": "0",
"geo_point": {
"lat": "43.65682410",
"lon": "-79.37617410"
},
"search_text_completion": {
"input": [
"Kyoto Katsugyu【京都勝牛】"
],
"contexts": {
"type": [
"video"
]
}
}
}
}
Any ideas why does it work like this?
Elasticsearch is taking long time to return records. I have total around 40000 records in the index. Previously I was using Mysql db which was taking around 30 seconds to return data then I moved to Elasticsearch for improving the search experience but Elasticssearch is also taking around 25 seconds.
here is my query
{
"query": {
"bool": {
"must": {
"match": {
"from_name_field_subject_content": "ups"
}
},
"should": [
{
"match": {
"from_name": "ups"
}
}
],
"boost": 1
}
},
"from": 0,
"size": 100
}
mapping
{
"mapping": {
"properties": {
"bcc_field": {
"type": "text"
},
"cc_field": {
"type": "text"
},
"con_us_id": {
"type": "long"
},
"created_by": {
"type": "long"
},
"created_by_group": {
"type": "long"
},
"created_on": {
"type": "date"
},
"ema_con_log_id": {
"type": "long"
},
"ema_rea_by_id": {
"type": "long"
},
"ema_ref_num_id": {
"type": "long"
},
"email_imap_unique_id": {
"type": "long"
},
"email_opened": {
"type": "keyword"
},
"email_opened_date": {
"type": "date"
},
"forward_from_email_id": {
"type": "keyword"
},
"from_field": {
"type": "text",
"copy_to": [
"from_name_field_subject_content"
]
},
"from_name": {
"type": "text",
"copy_to": [
"from_name_field_subject_content"
]
},
"from_name_field_subject_content": {
"type": "text"
},
"full_content": {
"type": "text",
"copy_to": [
"from_name_field_subject_content"
]
},
"in_reply_to": {
"type": "long"
},
"is_active": {
"type": "keyword"
},
"is_archived": {
"type": "keyword"
},
"is_delete": {
"type": "keyword"
},
"is_draft": {
"type": "keyword"
},
"is_flagged": {
"type": "keyword"
},
"is_invoice": {
"type": "keyword"
},
"is_junk": {
"type": "keyword"
},
"is_read": {
"type": "keyword"
},
"is_spam": {
"type": "keyword"
},
"recent_content": {
"type": "text"
},
"subject_field": {
"type": "text",
"copy_to": [
"from_name_field_subject_content"
]
},
"to_field": {
"type": "text"
},
"updated_on": {
"type": "date"
}
}
}
}
full_content is the field which contain a long text data (whole email content with html init)
Error
[body] => {"error":{"root_cause":[{"type":"mapper_parsing_exception","reason":"failed to parse"}],"type":"mapper_parsing_exception","reason":"failed to
parse","caused_by":{"type":"not_x_content_exception","reason":"Compressor detection can
only be called on some xcontent bytes or compressed xcontent ytes"}},"status":400}
I'm getting an error while adding the documents to my index.
http://localhost:9595/patient_trimester
{
"patient_trimester": {
"aliases": {
},
"mappings": {
"_default_": {
"_all": {
"enabled": true
},
"dynamic_templates": [
{
"string_fields": {
"mapping": {
"index": "not_analyzed",
"omit_norms": true,
"type": "string"
},
"match": "*",
"match_mapping_type": "string"
}
}
],
"properties": {
"#version": {
"type": "string",
"index": "not_analyzed"
}
}
},
"patient_trimester": {
"_all": {
"enabled": true
},
"dynamic_templates": [
{
"string_fields": {
"mapping": {
"index": "not_analyzed",
"omit_norms": true,
"type": "string"
},
"match": "*",
"match_mapping_type": "string"
}
}
],
"properties": {
"#timestamp": {
"type": "date",
"format": "strict_date_optional_time||epoch_millis"
},
"#version": {
"type": "string",
"index": "not_analyzed"
},
"last_consult_by": {
"type": "string",
"index": "not_analyzed"
},
"mpi": {
"type": "string",
"index": "not_analyzed"
},
"bill_id": {
"type": "integer"
},
"bill_date": {
"type": "date",
"format": "strict_date_optional_time||epoch_millis"
},
"site": {
"type": "string",
"index": "not_analyzed"
},
"effective_edd": {
"type": "date",
"format": "strict_date_optional_time||epoch_millis"
},
"is_converted": {
"type": "integer"
},
"admitting_physician": {
"type": "string",
"index": "not_analyzed"
},
"days": {
"type": "integer"
},
"trim": {
"type": "string",
"index": "not_analyzed"
},
"tags": {
"type": "string",
"index": "not_analyzed"
}
}
}
},
"warmers": {
}
}
}
This is how I created the index through postman.
in the $result variable im sending
(
[last_consult_by] => xxxxxx
[mpi] => xxxxxxxx
[bill_id] => 176073
[bill_date] => 2018-07-12 12:00:00
[site] => xxx
[effective_edd] => 2018-07-28 12:00:00
[is_converted] => 0
[admitting_physician] => xxxxxxxxx
[days] => 16
[trim] => Array
(
[trim3] => 1
)
)
$params = [
'index' => 'patient_trimester',
'type' => 'patient_trimester',
'body' => $result
];
$res = $client->index($params);
print_r($res); exit;
I'm not getting why mapper_parsing_exception is happening.
Is this because of my mapping of datatypes? mapping given for Datatype of effective_edd,bill_date and the trim is right ?
please help me out to resolve this issue.
I have a mapping like this
{
"settings": {
"analysis": {
"filter": {
"nGramFilter": {
"type": "nGram",
"min_gram": 3,
"max_gram": 20,
"token_chars": [
"letter",
"digit",
"punctuation",
"symbol"
]
},
"email" : {
"type" : "pattern_capture",
"preserve_original" : 1,
"patterns" : [
"([^#]+)",
"(\\p{L}+)",
"(\\d+)",
"#(.+)"
]
},
"number" : {
"type" : "pattern_capture",
"preserve_original" : 1,
"patterns" : [
"([^+-]+)",
"(\\d+)"
]
},
"edgeNGramFilter": {
"type": "nGram",
"min_gram": 1,
"max_gram": 10,
"token_chars": [
"letter",
"digit",
"punctuation",
"symbol"
]
}
},
"analyzer": {
"nGramAnalyzer": {
"type": "custom",
"tokenizer": "whitespace",
"filter": [
"lowercase",
"nGramFilter"
]
},
"whitespaceAnalyzer": {
"type": "custom",
"tokenizer": "whitespace",
"filter": [
"lowercase"
]
},
"email" : {
"tokenizer" : "uax_url_email",
"filter" : [
"email",
"lowercase",
"unique"
]
},
"number" : {
"tokenizer" : "whitespace",
"filter" : [ "number", "unique" ]
},
"edgeNGramAnalyzer": {
"type": "custom",
"tokenizer": "whitespace",
"filter": [
"lowercase",
"edgeNGramFilter"
]
}
}
}
},
"users": {
"mappings": {
"user_profiles": {
"properties": {
"firstName": {
"type": "string",
"analyzer": "nGramAnalyzer",
"search_analyzer": "whitespaceAnalyzer"
},
"lastName": {
"type": "string",
"analyzer": "nGramAnalyzer",
"search_analyzer": "whitespaceAnalyzer"
},
"email": {
"type": "string",
"analyzer": "email",
"search_analyzer": "whitespaceAnalyzer"
},
"score" : {
"type": "string"
},
"homeLandline": {
"type": "string",
"analyzer": "number",
"search_analyzer": "whitespaceAnalyzer"
},
"dob": {
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss"
},
"mobile": {
"type": "integer"
},
"residenceCity": {
"type": "string",
"analyzer": "edgeNGramAnalyzer",
"search_analyzer": "whitespaceAnalyzer"
},
"created_at": {
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss"
},
}
}
}
}
}
I can get the score as integer as well as "NA" so I mapped the type as string but while posting data to the index i am getting Number Format Exception.
For Example:
if I post first data as integer and followed by "NA". I am getting these exception.
while checking my log file I am getting this errors:
[2016-08-29 15:19:01] elasticlog.WARNING: Response ["{\"error\":{\"root_cause\":[{\"type\":\"mapper_parsing_exception\",\"reason\":\"failed
to parse
[score]\"}],\"type\":\"mapper_parsing_exception\",\"reason\":\"failed
to parse
[score]\",\"caused_by\":{\"type\":\"number_format_exception\",\"reason\":\"For
input string: \"NH\"\"}},\"status\":400}"] []
Your mapping is incorrect. It should be, assuming, users is the index name and user_profiles is the type:
{
"users": {
"mappings": {
"user_profiles": {
"properties": {
"score": {
"type": "string"
}
}
}
}
}
}
You have a missing mappings before user_profiles.
I have a JSON Schema for new orders, that consists of order list and address.
{
"$schema": "http://json-schema.org/draft-04/schema#",
"type": "array",
"properties": {
"order": {
"type": "array",
"items": {
"type": "array",
"properties": {
"product_id": {
"type": "integer"
},
"quantity": {
"type": "integer"
}
},
"required": [
"product_id",
"quantity"
]
}
},
"address": {
"type": "array",
"properties": {
"name": {
"type": "string"
},
"phone": {
"type": "integer"
},
"address1": {
"type": "string"
},
"address2": {
"type": "string"
},
"city": {
"type": "string"
},
"state_or_region": {
"type": "string"
},
"country": {
"type": "string"
}
},
"required": [
"name",
"phone",
"address1",
"city",
"state_or_region",
"country"
]
}
},
"required": [
"order",
"address"
]
}
But it doesn't seem to actually validate the items at all (I'm using Laravel 5.2 with "justinrainbow/json-schema": "~2.0" ):
$refResolver = new \JsonSchema\RefResolver(new \JsonSchema\Uri\UriRetriever(), new \JsonSchema\Uri\UriResolver());
$schema = $refResolver->resolve(storage_path('schemas\orders.post.json'));
$errors = [];
$input = Request::input();
// Validate
$validator = new \JsonSchema\Validator();
$validator->check($input, $schema);
$msg = [];
if ($validator->isValid()) {
return Response::json(['valid'], 200, [], $this->pritify);
} else {
$msg['success'] = false;
$msg['message'] = "JSON does not validate";
foreach ($validator->getErrors() as $error) {
$msg['errors'][] = [
'error' => ($error['property'] = ' ') ? 'wrong_data' : $error['property'],
'message' => $error['message']
];
}
return Response::json($msg, 422, [], $this->pritify);
}
A request like this always comes valid:
{
"order": [
{
"product_id": 100,
"quantity": 1
},
{
"product_id": 0,
"quantity": 2
}
],
"address": []
}
Any ideas what am I doing wrong?
You have messed array and object types. The only array value in your scheme must be order. Fixed scheme:
{
"$schema": "http://json-schema.org/draft-04/schema#",
"type": "object",
"properties": {
"order": {
"type": "array",
"items": {
"type": "object",
"properties": {
"product_id": {
"type": "integer"
},
"quantity": {
"type": "integer"
}
},
"required": [
"product_id",
"quantity"
]
}
},
"address": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"phone": {
"type": "integer"
},
"address1": {
"type": "string"
},
"address2": {
"type": "string"
},
"city": {
"type": "string"
},
"state_or_region": {
"type": "string"
},
"country": {
"type": "string"
}
},
"required": [
"name",
"phone",
"address1",
"city",
"state_or_region",
"country"
]
}
},
"required": [
"order",
"address"
]
}
And validation errors I got with you test data:
JSON does not validate. Violations:
[address.name] The property name is required
[address.phone] The property phone is required
[address.address1] The property address1 is required
[address.city] The property city is required
[address.state_or_region] The property state_or_region is required
[address.country] The property country is required