I want to insert 10000 data into the couchbase, but only part of data has been inserted successfully. I have tried several times and the number of data that has been inserted successfully is different everytime.
How can I insert all the data into couchbase?
bucket, _ := myCluster.OpenBucket("test", "")
for i := 0; i < 10000; i++ {
s := strconv.Itoa(i)
batch = append(batch, &gocb.ReplaceOp{Key: s, Value: "test"})
}
err = bucket.Do(batch)
There are two pictures about the bucket.
Bucket before operation:
Bucket after operation:
You could try dynamically writing a long N1QL query, of this form, but longer:
INSERT INTO test(KEY, VALUE) VALUES ("1", {"a": 1}), ("2", {"a": 2}), ("3", {"a": 3})
Related
Here is my json data:
{
"TransactionId": "1",
"PersonApplicant": [
{
"PersonalId": "1005",
"ApplicantPhone": [
{
"PhoneType": "LANDLINE",
"PhoneNumber": "8085063644",
"IsPrimaryPhone": true
}
]
},
{
"PersonalId": "1006",
"ApplicantPhone": [
{
"PhoneType": "LANDLINE",
"PhoneNumber": "9643645364",
"IsPrimaryPhone": true
},
{
"PhoneType": "HOME",
"PhoneNumber": "987654321",
"IsPrimaryPhone": false
}
]
}
]
}
I want to get phone no of the people who have phonetype as landline.
How to do that?
I tried this approach:
#find phoneNumber when phoneType='LANDLINE'
SELECT
#path_to_name := json_unquote(json_search(applicationData, 'one', 'LANDLINE')) AS path_to_name,
#path_to_parent := trim(TRAILING '.PhoneType' from #path_to_name) AS path_to_parent,
#event_object := json_extract(applicationData, #path_to_parent) as event_object,
json_unquote(json_extract(#event_object, '$.PhoneNumber')) as PhoneNumber
FROM application;
The issue with this is that I am using 'one' so I am able to achieve results but here in my json I have 2 people who have type as landline.
Using json search I am getting array of values and I am not able to decide how to extract these array row values in a manner where I can extract paths.
SELECT
#path_to_name := json_unquote(json_search(applicationData, 'all', 'LANDLINE')) from application;
result:
as you can see at 3rd and 4th row i am getting 2 data as an array.
How do I store this data to get the appropriate result?
I also tried one more query but not able to retrieve results for array of data.
I cannot use stored procedure and I have to use mysql workbench.
Please note that I am fresher so I don't know how I can approach this solution for more complex queries where I may have to retrieve id of a person having type as landline (multiple people in single array).
SELECT test.id, jsontable.*
FROM test
CROSS JOIN JSON_TABLE(test.data,
'$.PersonApplicant[*]'
COLUMNS ( PersonalId INT PATH '$.PersonalId',
PhoneType VARCHAR(255) PATH '$.ApplicantPhone[0].PhoneType',
PhoneNumber VARCHAR(255) PATH '$.ApplicantPhone[0].PhoneNumber')) jsontable
WHERE jsontable.PhoneType = 'LANDLINE';
https://dbfiddle.uk/?rdbms=mysql_8.0&fiddle=4089207ccfba5068a48e06b52865e759
I have a list of structs as follows
row = [
{
"name":<name1>,
"age" :<age1>,
"job" :<job1>
},
{
"name":<name1>,
"age" :<age1>,
"job" :<job1>
},
{
"name":<name1>,
"age" :<age1>,
"job" :<job1>
},
etc...
]
I want to insert this into an SQL table. So far I was running a loop through the array and inserting each row one by one. But is there any other way by which I can insert all the rows with just one query? I know bulk insert, but my understanding is that, for bulk insert, I will have to import data from an external file. I don't want to do that. How do I use the data from this array and perform bulk insert?
type Person struct {
Name string
Age int
Job string
}
func InsertPeople(db *sql.DB, personSlice []*Person) error {
var queryString = `INSERT INTO "person_table" (
"name"
, "age"
, "job"
) VALUES `
numOfFields := 3
params := make([]interface{}, len(personSlice)*numOfFields)
for i, p := range personSlice {
pos := i * numOfFields
params[pos+0] = p.Name
params[pos+1] = p.Age
params[pos+2] = p.Job
queryString += `(?, ?, ?),`
}
queryString = queryString[:len(queryString)-1] // drop last comma
_, err := db.Exec(queryString, params...)
return err
}
You aren't going to be able to do any kind of super-optimized bulk insert without placing a file on the server I don't think.
I am not sure if the db library supports it but using the SQLX extension you can build a single insert statement with named bindvars that go against a struct. You can then pass an array of these structs to a method like NamedExec.
Something like this:
users := []User{
{
Name: "alex",
Email: "alex#example.com",
},
{
Name: "muhammed",
Email: "muhammed#example.com",
},
}
db.NamedExec("insert into users (NAME, EMAIL) values (:Name, :Email);", users)
I'm using the latest cassandra version and trying to save JSON like below and was successful,
INSERT INTO mytable JSON '{"username": "myname", "country": "mycountry", "userid": "1"}'
Above query saves the record like,
"rows": [
{
"[json]": "{\"userid\": \"1\", \"country\": \"india\", \"username\": \"sai\"}"
}
],
"rowLength": 1,
"columns": [
{
"name": "[json]",
"type": {
"code": 13,
"type": null
}
}
]
Now I would like to retrieve the record based on userid:
SELECT JSON * FROM mytable WHERE userid = fromJson("1") // but this query throws error
All this occurs in a node/express app and I'm using dse-driver as the client driver.
The CQL command worked like below,
SELECT JSON * FROM mytable WHERE userid="1";
However if it has to be executed via the dse-driver then the below snippet worked,
let query = 'SELECT JSON * FROM mytable WHERE userid = ?';
client.execute(query, ["1"], { prepare: true });
where client is,
const dse = require('dse-driver');
const client = new dse.Client({
contactPoints: ['h1', 'h2'],
authProvider: new dse.auth.DsePlainTextAuthProvider('username', 'pass')
});
If your Cassandra version is 2.1x and below, you can use the Python-based approach. Write a python script using Cassandra-Python API
Here you have to get your row first and then use python json's loads method, which will convert your json text column value into JSON object which will be dict in Python. Then you can play around with Python dictionaries and extract your required nested keys. See the below code snippet.
from cassandra.cluster import Cluster
from cassandra.auth import PlainTextAuthProvider
import json
if __name__ == '__main__':
auth_provider = PlainTextAuthProvider(username='xxxx', password='xxxx')
cluster = Cluster(['0.0.0.0'],
port=9042, auth_provider=auth_provider)
session = cluster.connect("keyspace_name")
print("session created successfully")
rows = session.execute('select * from user limit 10')
for user_row in rows:
#fetchign your json column
column_dict = json.loads(user_row.json_col)
print(column_dict().keys()
Assuming user-id is the partition key, and assuming you want to retrieve a JSON object corresponding to user of id 1, you should try:
SELECT JSON * FROM mytable WHERE userid=1;
If userid is of type text, you will need to add some quotes.
So I have a lot of json files structured like this:
{
"Id": "2551faee-20e5-41e4-a7e6-57bd20b02a22",
"Timestamp": "2016-12-06T08:09:57.5541438+01:00",
"EventEntry": {
"EventId": 1,
"Payload": [
"1a3e0c9e-ef69-4c6a-ac8c-9b2de2fbc701",
"DHS.PlanCare.Business.BusinessLogic.VisionModels.VisionModelServiceWithoutUnitOfWork.FetchVisionModelsForClientOnReferenceDateAsync(System.Int64 clientId, System.DateTime referenceDate, System.Threading.CancellationToken cancellationToken)",
25,
"DHS.PlanCare.Business.BusinessLogic.VisionModels.VisionModelServiceWithoutUnitOfWork+<FetchVisionModelsForClientOnReferenceDateAsync>d__11.MoveNext\r\nDHS.PlanCare.Core.Extensions.IQueryableExtensions+<ExecuteAndThrowTaskCancelledWhenRequestedAsync>d__16`1.MoveNext\r\n",
false,
"2197, 6-12-2016 0:00:00, System.Threading.CancellationToken"
],
"EventName": "Duration",
"KeyWordsDescription": "Duration",
"PayloadSchema": [
"instanceSessionId",
"member",
"durationInMilliseconds",
"minimalStacktrace",
"hasFailed",
"parameters"
]
},
"Session": {
"SessionId": "0016e54b-6c4a-48bd-9813-39bb040f7736",
"EnvironmentId": "C15E535B8D0BD9EF63E39045F1859C98FEDD47F2",
"OrganisationId": "AC6752D4-883D-42EE-9FEA-F9AE26978E54"
}
}
How can I create an u-sql query that outputs the
Id,
Timestamp,
EventEntry.EventId and
EventEntry.Payload[2] (value 25 in the example below)
I can't figure out how to extend my query
#extract =
EXTRACT
Timestamp DateTime
FROM #"wasb://xxx/2016/12/06/0016e54b-6c4a-48bd-9813-39bb040f7736/yyy/{*}/{*}.json"
USING new Microsoft.Analytics.Samples.Formats.Json.JsonExtractor();
#res =
SELECT Timestamp
FROM #extract;
OUTPUT #res TO "/output/result.csv" USING Outputters.Csv();
I have seen some examples like:
U- SQL Unable to extract data from JSON file => this only queries one level of the document, I need data from multiple levels.
U-SQL - Extract data from json-array => this only queries one level of the document, I need data from multiple levels.
JSONTuple supports multiple JSONPaths in one go.
#extract =
EXTRACT
Id String,
Timestamp DateTime,
EventEntry String
FROM #"..."
USING new Microsoft.Analytics.Samples.Formats.Json.JsonExtractor();
#res =
SELECT Id, Timestamp, EventEntry,
Microsoft.Analytics.Samples.Formats.Json.JsonFunctions.JsonTuple(EventEntry,
"EventId", "Payload[2]") AS Event
FROM #extract;
#res =
SELECT Id,
Timestamp,
Event["EventId"] AS EventId,
Event["Payload[2]"] AS Something
FROM #res;
You may want to look at this GIT example. https://github.com/Azure/usql/blob/master/Examples/JsonSample/JsonSample/NestedJsonParsing.usql
This take 2 disparate data elements and combines them, like you have the Payload, and Payload schema. If you create key value pairs using the "Donut" or "Cake and Batter" examples you may be able to match the scema up to the payload and use the cross apply explode function.
I have a column of text type be contain JSON value.
{
"customer": [
{
"details": {
"customer1": {
"name": "john",
"addresses": {
"address1": {
"line1": "xyz",
"line2": "pqr"
},
"address2": {
"line1": "abc",
"line2": "efg"
}
}
}
"customer2": {
"name": "robin",
"addresses": {
"address1": null
}
}
}
}
]
}
How can I extract 'address1' JSON field of column with query?
First I am trying to fetch JSON value then I will go with parsing.
SELECT JSON customer from text_column;
With my query, I get following error.
com.datastax.driver.core.exceptions.SyntaxError: line 1:12 no viable
alternative at input 'customer' (SELECT [JSON] customer...)
com.datastax.driver.core.exceptions.SyntaxError: line 1:12 no viable
alternative at input 'customer' (SELECT [JSON] customer...)
Cassandra version 2.1.13
You can't use SELECT JSON in Cassandra v2.1.x CQL v3.2.x
For Cassandra v2.1.x CQL v3.2.x :
The only supported operation after SELECT are :
DISTINCT
COUNT (*)
COUNT (1)
column_name AS new_name
WRITETIME (column_name)
TTL (column_name)
dateOf(), now(), minTimeuuid(), maxTimeuuid(), unixTimestampOf(), typeAsBlob() and blobAsType()
In Cassandra v2.2.x CQL v3.3.x Introduce : SELECT JSON
With SELECT statements, the new JSON keyword can be used to return each row as a single JSON encoded map. The remainder of the SELECT statment behavior is the same.
The result map keys are the same as the column names in a normal result set. For example, a statement like “SELECT JSON a, ttl(b) FROM ...” would result in a map with keys "a" and "ttl(b)". However, this is one notable exception: for symmetry with INSERT JSON behavior, case-sensitive column names with upper-case letters will be surrounded with double quotes. For example, “SELECT JSON myColumn FROM ...” would result in a map key "\"myColumn\"" (note the escaped quotes).
The map values will JSON-encoded representations (as described below) of the result set values.
If your Cassandra version is 2.1x and below, you can use the Python-based approach.
Write a python script using Cassandra-Python API
Here you have to get your row first and then use python json's loads method, which will convert your json text column value into JSON object which will be dict in Python. Then you can play around with Python dictionaries and extract your required nested keys. See the below code snippet.
from cassandra.cluster import Cluster
from cassandra.auth import PlainTextAuthProvider
import json
if __name__ == '__main__':
auth_provider = PlainTextAuthProvider(username='xxxx', password='xxxx')
cluster = Cluster(['0.0.0.0'],
port=9042, auth_provider=auth_provider)
session = cluster.connect("keyspace_name")
print("session created successfully")
rows = session.execute('select * from user limit 10')
for user_row in rows:
customer_dict = json.loads(user_row.customer)
print(customer_dict().keys()