I have an AWS DynamoDb cart table with the following item structure -
{
"cart_id": "5e4d0f9f-f08c-45ae-986a-f1b5ac7b7c13",
"user_id": 1234,
"type": "OTHER",
"currency": "INR",
"created_date": 132432423,
"expiry": 132432425,
"total_amount": 90000,
"total_quantity": 2,
"items": [
{
"amount": 90000,
"category": "Laptops",
"name": "Apple MacBook Pro",
"quantity": 1
}
]
}
-
{
"cart_id": "12340f9f-f08c-45ae-986a-f1b5ac7b1234",
"user_id": 1234,
"type": "SPECIAL",
"currency": "INR",
"created_date": 132432423,
"expiry": 132432425,
"total_amount": 1000,
"total_quantity": 2,
"items": [
{
"amount": 1000,
"category": "Special",
"name": "Special Item",
"quantity": 1
}
]
}
The table will have cart_id as Primary key,
user_id as an Index or GSI,
type as an Index or GSI.
I want to be able to query the cart table,
to find the items which have user_id = 1234 AND type != "SPECIAL".
I don't know if this means for the query -
--key-condition-expression "user_id = 1234 AND type != 'SPECIAL'"
I understand that an AWS DynamoDb table cannot be queried using multiple indexes at the same time,
I came across the following question, it has a similar use case and the answer is recommending creating a composite key,
Querying with multiple local Secondary Index Dynamodb
Does it mean that while putting a new item in the table,
I will need to maintain another column like user_id_type,
with its value as 1234SPECIAL and create an Index / GSI for user_id_type ?
Sample item structure -
{
"cart_id": "5e4d0f9f-f08c-45ae-986a-f1b5ac7b7c13",
"user_id": 1234,
"type": "OTHER",
"user_id_type" : "1234OTHER",
"currency": "INR",
"created_date": 132432423,
"expiry": 132432425,
"total_amount": 90000,
"total_quantity": 2,
"items": [
{
"amount": 90000,
"category": "Laptops",
"name": "Apple MacBook Pro",
"quantity": 1
}
]
}
References -
1. Querying with multiple local Secondary Index Dynamodb
2. Is there a way to query multiple hash keys in DynamoDB?
Your assumption is correct. Maybe you can add into that a delimitter field1_field2 or hash them if either of them is too big in size hashOfField1_hashOfField2
That mean spending some more processing power on your side, however. As DynamoDB does not natively support It.
Composite key in DynamoDB with more than 2 columns?
Dynamodb: query using more than two attributes
Additional info on your use case
KeyConditionExpression only allowed for the hash key.
You can put it in the FilterExpression
Why is there no **not equal** comparison in DynamoDB queries?
Does it mean that while putting a new item in the table,
I will need to maintain another column like user_id_type,
with its value as 1234SPECIAL and create an Index / GSI for user_id_type?
The answer is it depends on how many columns (dynamodb is schema-less, by a column I mean data field) you need and are you happy with 2 round trips to DB.
your query:
user_id = 1234 AND type != "SPECIAL"
1- if you need all information in the cart but you are happy with two round trips:
Solution: Create a GSI with user_id (HASH) and type (RANGE), then add cart_id (base table Hash key) as projection.
Explanation: so, you need one query on index table to get the cart_id given user_id and type
--key-condition-expression "user_id = 1234 AND type != 'SPECIAL'"
then you need to use cart_id(s) from the result and make another query to the base table
2- if you do not need all of cart information.
Solution: you need to create a GSI and make user_id HASH and type as RANGE and add more columns (columns you need) to projections.
Explanation: projection is additional columns you want to have in your index table. So, add some extra columns, which are more likely to be used as a result of the query, to avoid an extra round trip to the base table
Note: adding too many extra columns can double your costs, as any update on base table results in updates in GSI tables projection fields)
3- if you want just one round trip and you need all data
then you need to manage it by yourself and your suggestion can be applied
One possible answer is to create a single index with a sort key. Then you can do this:
{
TableName: "...",
IndexName: "UserIdAndTypeIndex",
KeyConditionExpression: "user_id = :user_id AND type != :type",
ExpressionAttributeValues: {
":user_id": 1234,
":type": "SPECIAL"
}
}
You can build GraphQL schema with AWS AppSync from your DynamoDB table and than query it in your app with GraphQL. Link
Related
This question is a follow up to another SO question.
Summary: I have an API returning a nested JSON array. Data is being extracted via APEX REST Data Sources. The Row Selector in the Data Profile is set to "." (to select the "root node").
The lines array has been manually added to a column (LINES) to the Data Profile, set data type to JSON Document, and used lines as the selector.
SAMPLE JSON RESPONSE FROM API
[ {
"order_number": "so1223",
"order_date": "2022-07-01",
"full_name": "Carny Coulter",
"email": "ccoulter2#ovh.net",
"credit_card": "3545556133694494",
"city": "Myhiya",
"state": "CA",
"zip_code": "12345",
"lines": [
{
"product": "Beans - Fava, Canned",
"quantity": 1,
"price": 1.99
},
{
"product": "Edible Flower - Mixed",
"quantity": 1,
"price": 1.50
}
]
},
{
"order_number": "so2244",
"order_date": "2022-12-28",
"full_name": "Liam Shawcross",
"email": "lshawcross5#exblog.jp",
"credit_card": "6331104669953298",
"city": "Humaitá",
"state": "NY",
"zip_code": "98670",
"lines": [
{
"order_id": 5,
"product": "Beans - Green",
"quantity": 2,
"price": 4.33
},
{
"order_id": 1,
"product": "Grapefruit - Pink",
"quantity": 5,
"price": 5.00
}
]
},
]
The order attributes have been synchronized to a local table (Table name: SOTEST_LOCAL)
The table has the correct data. As you can see below, the LINES column contains the JSON array.
I then created an ORDER_LINES child table to extract the JSON from LINES column in the SOTEST_LOCAL table. (Sorry for the table names.. I should've named the tables as ORDERS_LOCAL and ORDER_LINES_LOCAL)
CREATE TABLE "SOTEST_ORDER_LINES_LOCAL"
( "LINE_ID" NUMBER,
"ORDER_ID" NUMBER,
"LINE_NUMBER" NUMBER,
"PRODUCT" VARCHAR2(200) COLLATE "USING_NLS_COMP",
"QUANTITY" NUMBER,
"PRICE" NUMBER,
CONSTRAINT "SOTEST_ORDER_LINES_LOCAL_PK" PRIMARY KEY ("LINE_ID")
USING INDEX ENABLE
) DEFAULT COLLATION "USING_NLS_COMP"
/
ALTER TABLE "SOTEST_ORDER_LINES_LOCAL" ADD CONSTRAINT "SOTEST_ORDER_LINES_LOCAL_FK" FOREIGN KEY ("ORDER_ID")
REFERENCES "SOTEST_LOCAL" ("ORDER_ID") ON DELETE CASCADE ENABLE
/
QuickSQL version..
SOTEST_ORDER_LINES_LOCAL
LINE_ID /pk
ORDER_ID /fk SOTEST_LOCAL references ORDER_ID
LINE_NUMBER
PRODUCT
QUANTITY
PRICE
So per Carsten's answer in the previous question, I can write SQL to extract the JSON array from the LINES column in the SOTEST_LOCAL table to the child table SOTEST_ORDER_LINES_LOCAL.
My question is two parts.
Where exactly do I write the SQL? Would I write it in SQL Workshop in SQL Commands?
The REST data is being synchronized to make a request every hour. So would I need to write a function that runs every time there is new data being merged?
there are multiple options for this:
Create a trigger on the local synchronization table
You could create an trigger on your ORDERS table, which runs AFTER INSERT, UPDATE or DELETE on your ORDERS table, and which maintains the LINES table. The nice things about this one is that the maintenance of the child table is independent from APEX or the REST Synchronization; it would also work if you just inserted rows with plain SQL*Plus.
Here's some pseudo-code on how the trigger could look like.
create or replace trigger tr_maintain_lines
after insert or update or delete on ORDERS_LOCAL
for each row
begin
if inserting then
insert into SOTEST_ORDER_LINES_LOCAL ( order_id, line_id, line_number, product, quantity, price)
( select :new.id,
seq_lines.nextval,
j.line#,
j.product,
j.quantity,
j.price
from json_table(
:new.lines,
'$[*]' columns (
line# for ordinality,
product varchar2(255) path '$.product',
quantity number path '$.quantity',
price number path '$.price' ) ) );
elsif deleting then
delete SOTEST_ORDER_LINES_LOCAL
where order_id = :old.id;
elsif updating then
--
-- handle the update case here.
-- I would simply delete and re-insert LINES rows.
end if;
end;
Handle child table maintenance in APEX itself.
You could turn off the schedule of your REST Source synchronization, and have it only running when called with APEX_REST_SOURCE_SYNC.SYNCHRONIZE_DATA (https://docs.oracle.com/en/database/oracle/apex/22.1/aeapi/SYNCHRONIZE_DATA-Procedure.html#GUID-660DE4D1-4BAF-405A-A871-6B8C201969C9).
Then create an APEX Automation, which runs on your desired schedule, and this automation has two Actions. One would be the REST Source Synchronization, the other one would call PL/SQL code to maintain the child tables.
Have a look into this blog posting which talks a bit about more complex synchronization scenarios (although it does exactly fit scenario): https://blogs.oracle.com/apex/post/synchronize-parent-child-rest-sources
I hope this helps
Is it possible to use multiple sort values in aws sdk dynamodb batchGetItem using one query? My aim is to be able to query the result of multiple sort keys? Or how is an efficient way of doing such a query?
E.g
Partition key / Sort key
A 1
A 2
B 3
E.g input A and 1 and 2
BatchGetItem requires you to specify the full primary key. That means you'd need to specify the partition key and the sort key at the same time.
For example, you could do the following (in pseudocode):
ddbclient.batchGetItem({
{
"RequestItems": {
"YOUR_TABLE_NAME": {
"Keys": [
{
"PK":{"S":"A"},
"SK":{"N": 1},
},
{
"PK":{"S":"A"},
"SK":{"N": 2},
},
]
}
}
})
However, if you do not know the sort key and watch to fetch all the items with Partition Key = "A", you should use the query operation. The query operation does not require you to specify the sort key.
dynamoDbLib.query({
TableName: "YOUR_TABLE_NAME",
KeyConditionExpression: "PK = A",
});
I want to query a DDB GSI with key condition, and apply filter on returned result using contains function.
Data I have in DDB table:
{
"lookupType": "PRODUCT_GROUP",
"name": "Spring framework study set",
"structureJson": {
"productIds": [
"FBCUPOQsrp",
"Y4LDaiViLY",
"J6N3UWq9CK"
]
},
"ownerId": "mT9R9y6zGO"
}
{
"lookupType": "PRODUCT_GROUP",
"name": "Relational databases study set",
"structureJson": {
"productIds": [
"QWQWQWQWQW",
"XZXZXZXZXZ"
]
},
"ownerId": "mT9R9y6zGO"
}
...
I have a compound GSI (ownerId - HASH, lookupType - RANGE).
When I try to query the DDB (query structure is in "2" field) I get the result (the result is in "3"):
{
"0":[
],
"2":{
"TableName":"Products",
"IndexName":"ProductsOwnerIdLookupTypeIndex",
"KeyConditionExpression":"#ownerId = :ownerId and #lookupType = :lookupType",
"FilterExpression":"contains(#structureMember, :memberId)",
"ExpressionAttributeNames":{
"#ownerId":"ownerId",
"#lookupType":"lookupType",
"#structureMember":"structureJson.productIds"
},
"ExpressionAttributeValues":{
":ownerId":"mT9R9y6zGO",
":lookupType":"PRODUCT_GROUP",
":memberId":"FBCUPOQsrp"
}
},
"3":{
"Items":[
],
"Count":0,
"ScannedCount":2
}
}
The returned result set is empty, despite I have data with given field values.
How I see the query (or what I want to achieve):
When I query the GSI with ownerId = mT9R9y6zGO and lookupType = PRODUCT_GROUP it will find 2 items - Spring and Relational DB sets
As the second step DDB will scan the returned query result with contains (structureJson.productIds, FBCUPOQsrp) filter expression and it should return one result to me, but I get empty set
Is something wrong with the query or do I miss some point in DDB query workflow?
Here is the situation:
My BigQuery TableSchema is as follows:
{
"name": "Id",
"type": "INTEGER",
"mode": "nullable"
},
{
"name": "Address",
"type": "RECORD",
"mode": "repeated",
"fields":[
{
"name": "Street",
"type": "STRING",
"mode": "nullable"
},
{
"name": "City",
"type": "STRING",
"mode": "nullable"
}
]
}
I am reading data from a Google Cloud Storage Bucket and writing in to BigQuery using a cloud function.
I have defined TableSchema in my cloud function as:
table_schema = bigquery.TableSchema()
Id_schema = bigquery.TableFieldSchema()
Id_schema.name = 'Id'
Id_schema.type = 'INTEGER'
Id_schema.mode = 'nullable'
table_schema.fields.append(Id_schema)
Address_schema = bigquery.TableFieldSchema()
Address_schema.name = 'Address'
Address_schema.type = 'RECORD'
Address_schema.mode = 'repeated'
Street_schema = bigquery.TableFieldSchema()
Street_schema.name = 'Street'
Street_schema.type = 'STRING'
Street_schema.mode = 'nullable'
Address_schema.fields.append(Street_schema)
table_schema.fields.append(Address_schema)
City_schema = bigquery.TableFieldSchema()
City_schema.name = 'City'
City_schema.type = 'STRING'
City_schema.mode = 'nullable'
Address_schema.fields.append(City_schema)
table_schema.fields.append(Address_schema)
My data file looks like this: (each row is json)
{"Id": 1, "Address": {"Street":"MG Road","City":"Pune"}}
{"Id": 2, "Address": {"City":"Mumbai"}}
{"Id": 3, "Address": {"Street":"XYZ Road"}}
{"Id": 4}
{"Id": 5, "PhoneNumber": 12345678, "Address": {"Street":"ABCD Road", "City":"Bangalore"}}
Question:
How can I handle when the incoming data has some missing keys?
e.g.,
On row #2 of the data "Street" is missing
On row #3 of the data "City" is missing
On row #4 of the data "Address" is missing
On row #5 of the data "PhoneNumber" shows up..
Question 1: How to handle WriteToBigQuery if the data in missing (e.g., row #2,#3,#4)
Question 2: How to handle if a new field shows up in the data?
e.g.,
On row #5 "PhoneNumber" shows up..
How can I add a new column in BigQuery table on the fly?
(Do I have have to define the BigQuery table schema exhaustive enough at first in order to accommodate such newly added fields?)
Question 3: How can I iterate through each row (while reading data file) of the incoming data file and determine which fields to parse?
One of the option for you is - instead of straggling with schema changes I would recommend to write your data into table with just one field line of type string - and apply schema logic on fly during the querying
Below example is for BigQuery Standard SQL of how to apply schema on fly against table with whole row in one field
#standardSQL
WITH t AS (
SELECT '{"Id": 1, "Address": {"Street":"MG Road","City":"Pune"}}' line UNION ALL
SELECT '{"Id": 2, "Address": {"City":"Mumbai"}}' UNION ALL
SELECT '{"Id": 3, "Address": {"Street":"XYZ Road"}}' UNION ALL
SELECT '{"Id": 4} ' UNION ALL
SELECT '{"Id": 5, "PhoneNumber": 12345678, "Address": {"Street":"ABCD Road", "City":"Bangalore"}}'
)
SELECT
JSON_EXTRACT_SCALAR(line, '$.Id') id,
JSON_EXTRACT_SCALAR(line, '$.PhoneNumber') PhoneNumber,
JSON_EXTRACT_SCALAR(line, '$[Address].Street') Street,
JSON_EXTRACT_SCALAR(line, '$[Address].City') City
FROM t
with result as below
Row id PhoneNumber Street City
1 1 null MG Road Pune
2 2 null null Mumbai
3 3 null XYZ Road null
4 4 null null null
5 5 12345678 ABCD Road Bangalore
I think this approach answers/addresses all your four questions
Question: How can I handle when the incoming data has some missing keys?
Question 1: How to handle WriteToBigQuery if the data in missing (e.g., row #2,#3,#4)
Question 2: How to handle if a new field shows up in the data?
I recommend decoding the JSON string to some data structure, for example a custom Contact class, where you can access and manipulate member variables and define which members are optional and which are required. Using a custom class gives you a level of abstraction so that downstream transforms in the pipeline don't need to worry about how to manipulate JSON. A downstream transform can be implemented to build a TableRow from a Contact object and also adhere to the BigQuery table schema. This design follows general abstraction and separation of concerns principles and is able to handle all scenarios of missing or additional fields.
Question 3: How can I iterate through each row (while reading data file) of the incoming data file and determine which fields to parse?
Dataflow's execution of the pipeline does this automatically. If the pipeline reads from Google Cloud Storage (using TextIO for example), then Dataflow will process each line of the file as an individual element (individual JSON string). Determining which fields to parse is a detail of the business logic and can be defined in a transform which parses the JSON string.
I think I'm misunderstanding DynamoDb. I would like to query for all items, with a child field of the json, which match an identifier I'm passing. The structure is something like -
{
"messageId": "ced96cab-767e-509198be5-3d2896a3efeb",
"identifier": {
"primary": "9927fd47-5d33-4f51-a5bb-f292a0c733b1",
"secondary": "none",
"tertiary": "cfd96cab-767e-5091-8be5-3d2896a3efeb"
},
"attributes": {
"MyID": {
"Type": "String",
"Value": "9927fd47-5c33-4f51-a5bb-f292a0c733b1"
}
}
}
I would like to query for all items in DynamoDb that has a value of MyID that I'm passing. Everything I've read seems to say you need to use the key which in my case is the messageId, this is unique for each entry and not a value I can use.
Hope this makes sense.
The DynamoDB Query API can be used only if you know the value of Partition key. Otherwise, you may need to scan the whole table using FilterExpression to find the item.
Scanning tables
You can create GSI on scalar attribute only. In the above case, it is a document data type (i.e. MAP). So, GSI can't be created.