InfluxDB With GoLang - database

I'm very new to InfluxDB and seem to be having some trouble understanding how to use the Go client. I'm currently using the default example code but I can't understand where to find the data that is being uploaded, or if it is being uploaded at all. The current code looks like
package main
import (
"context"
"fmt"
"time"
influxdb2 "github.com/influxdata/influxdb-client-go/v2"
)
func main() {
token := "tokenInsertedHere"
fmt.Println("testing influxdb")
// Create a new client using an InfluxDB server base URL and an authentication token
client := influxdb2.NewClient("http://localhost:8086", token)
// Use blocking write client for writes to desired bucket
writeAPI := client.WriteAPIBlocking("orgName", "bucketName")
// Create point using full params constructor
p := influxdb2.NewPoint("test",
map[string]string{"unit": "temperature"},
map[string]interface{}{"avg": 24.5, "max": 45.0},
time.Now())
// write point immediately
writeAPI.WritePoint(context.Background(), p)
client.Close()
}
When I'm on the data explorer page filtering measurements in the bucket the code should've wrote to, the measurement doesn't pop up. What am I doing wrong? I've noticed that the client doesn't throw any errors, which is strange to me. I've tried using a fake token and it acts like there were no problems when writing to the db. Would appreciate any help!

I can't conclusively know if this is your issue, but keeping my token and org names lined up correctly always trips me up. In the Influx web client, go to "Switch Organizations" and verify that the organization that you are using matches the organization selected in the web client. Hopefully this helps.

Change the line with write to catch an error and check what error occured:
err := writeAPI.WritePoint(context.Background(), p)
if err != nil {
panic(err)
}

Related

How to transalte messages that comes from server in react native app

I'm building a react-native app with spanish as default language, the problem is that I'm using a open source backend service to serve data and this data comes is in english by default. What I want is to transalate this data/messages that comes from server in my react-native app to show to the user the messages in spanish not in english.
This is the first time I am doing this process and it is not clear to me what are the steps or the flow that is generally followed for this kind of proces(translate messages that comes from server in my app).
You have many approaches to such a thing one comes to mind is
Catch the error/api response message which mostly server error messages comes in codes and messages.
set a condition statement if code equal 2 that means the server is down for example
Example:
You made a request to the server and there was an error with the server let say wrong username and password, now the server returns a message and a error code you have to get the code or the message and show your own message
.....made the request the server returned
{ code: 192, message: Wrong username/Password }
now in your code you will do the following
if(code == 192){
...do your message
}
P.S this is just on top my head since you didn't share any codes or responses from your server.
UPDATE :
If you want to translate all your strings/messages that comes from the server you would need to do another approche something like this
Create a file contain all the strings/codes from the server
compare messages/code comes from the server and the file will return the text you want
{ "102": "Hola", "103": "Bien", "104": "Nada", "105": "Si", }
now this file contain the error/message code all you have to do is when you receive the code grab the message from this file
let translation = {
"101": "Hola",
"102":"Si"
};
translation["102"]; // Result will be Si
Now this is the most accurate approach but you have to know all the messages/codes comes from the server, now if you want something to translate on the fly you might wanna use translation library and may not be accurate translation

How to properly add OAuth headers for a QuickBooks API call in Google Go

I am just trying to get a proof of concept working to test a connection to the QB api for a QB Online account. I have never tried to make an OAuth connection before like this, so I'm not sure that I am doing it right. Here's what I have so far, and it makes the request but I get a 401 error returned from QB's server (Unauthorized OAuth Token: signature_invalid401SERVER):
client := &http.Client{}
if req, err := http.NewRequest("GET", "https://qbo.intuit.com/qbo1/resource/customers/v2/717594130", nil); err != nil {
//handle error
} else {
req.Header.Add("Authorization", "OAuth oauth_token=\"MY_TOKEN\",oauth_nonce=\"7758caa9-e1f4-4fa1-84c5-5759fd513a88\",oauth_consumer_key=\"MY_KEY\",oauth_signature_method=\"HMAC-SHA1\",oauth_timestamp=\"1369259523\",oauth_version=\"1.0\",oauth_signature=\"MY_SIG\"")
if resp, err := client.Do(req); err != nil {
//handle error
} else {
defer resp.Body.Close()
contents, err := ioutil.ReadAll(resp.Body)
if err != nil {
//handle error
}
myOutput := string(contents)
}
}
Could the problem may be with my settings on my QB account instead? There is a setting for "Host Name Domain" that I think it might only allow connections from what I have entered there (which is currently intuit.com). If that is the case, how do I set that to allow connections from my dev app on my localhost?
Are you using the correct OAuth algorithm to generate the signature?
Can you post an actual request/response that shows the outgoing signature/OAuth header, and the response you get back from Intuit?
Your code doesn't show any of that, and it doesn't look like you're using an Intuit DevKit, so that's probably the place to start. My guess would be that the signature you're sending isn't valid. I would highly recommend you find a OAuth library, and use that OAuth library, rather than try to roll your own OAuth algorithm.
As far as this goes:
Could the problem may be with my settings on my QB account instead?
There is a setting for "Host Name Domain" that I think it might only
allow connections from what I have entered there (which is currently
intuit.com).
That is not likely to be the problem... but to get any further than a simple test request, you will need to set that to your host name. If it's a local dev box, you can enter your local dev boxes hostname (e.g. http://localhost/ or http://192.168.1.2/ or anything like that is fine - whatever URL you use to hit your dev box)

Get auth token in Gatling

I'm trying to use Gatling to test my API but I've got a problem. I'm testing for now the login/logout. At the login, the user got a token, that is used for logout.
When I use the recorder, it keep a fix token, and of course, it doesn't work when I run the test. But I don't find in the doc or google how I can get dynamically the token.
Does anyone know ?
Thanks !
EDIT:
after recording here what I got
val headers_13 = Map(
"Accept" -> """*/*""",
"Origin" -> """http://site.com""",
"token" -> """token"""
)
val scn = scenario("Scenario Name")
.exec(http("request_1")
.post("http://site.com/login")
.headers(headers_1)
.param("""player[email]""", """email#address.com""")
.param("""player[password]""", """password""")
)
.pause(757 milliseconds)
…
.exec(http("request_13")
.get("http://site.com/logout")
.headers(headers_13)
)
.pause(202 milliseconds)
I try to put the two pieces of code after .post("http://site.com/login") and .get("http://site.com/logout") but that didn't works
Where is your token? Is it a HTTP header?
Generally speaking, the way to save data from responses in order to reuse it for further requests is the Check API.
.check(header("tokenName").saveAs("token")
...
.header("tokenName", "${token}")

D3 Connection issue using mvsp java api

I am trying to connect to D3 Database with MVSP java api. So far:
I have downloaded the mvapi.jar
added it in project lib folder
written the sample code for connection inside main method
String url = "jdbc:mv:d3:hostname:portNo";
Properties props = new Properties();
props.setProperty("username", "");
props.setProperty("password", "");
String account = "AGCO";
String password = "";
MVConnection connection = null;
try {
// Getting error at this point
connection = new MVConnection(url,props);
MVStatement mvStatement = connection.createStatement();
connection.logTo(account,password);
MVResultSet results = mvStatement.executeQuery(query);
}
com.tigr.mvapi.exceptions.MVException: server error with errorCode 1023.
I checked the console but I'm not able to figure out the actual cause or whether I am entering the wrong username, password.
Please suggest what I am doing wrong.
First, you have to set a breakpoint or trace which function is throwing the errors. Then check the routes, (FileName) probably you will have much more experience than I do, but keep in mind that giving the full route ("account,filename," where the last comma is important) is never a bad idea while keep you safer and is mandatory if the filename is in a different account that you are logged to.
And like always please verify these things:
You have enough licenses. Try to close any terminal you have opened for testing your queries. Yes you know is true. One connection one license. Sometimes MVSP let you two under the same IP but chek this.
MVSP service is running. See Pick D3 documentation.
Your USER and ACCOUNT are both ENABLED to access in the MVSP server otherwise you won't be able to access these files or login with the user through the API. See the documentation to enable in the MVSP.Menu account.
I hope this helps.

How to delete all datastore in Google App Engine?

Does anyone know how to delete all datastore in Google App Engine?
If you're talking about the live datastore, open the dashboard for your app (login on appengine) then datastore --> dataviewer, select all the rows for the table you want to delete and hit the delete button (you'll have to do this for all your tables).
You can do the same programmatically through the remote_api (but I never used it).
If you're talking about the development datastore, you'll just have to delete the following file: "./WEB-INF/appengine-generated/local_db.bin". The file will be generated for you again next time you run the development server and you'll have a clear db.
Make sure to clean your project afterwards.
This is one of the little gotchas that come in handy when you start playing with the Google Application Engine. You'll find yourself persisting objects into the datastore then changing the JDO object model for your persistable entities ending up with obsolete data that'll make your app crash all over the place.
The best approach is the remote API method as suggested by Nick, he's an App Engine engineer from Google, so trust him.
It's not that difficult to do, and the latest 1.2.5 SDK provides the remote_shell_api.py out of the shelf. So go to download the new SDK. Then follow the steps:
connect remote server in your commandline: remote_shell_api.py yourapp /remote_api
The shell will ask for your login info, and if authorized, will make a Python shell for you. You need setup url handler for /remote_api in your app.yaml
fetch the entities you'd like to delete, the code looks something like:
from models import Entry
query = Entry.all(keys_only=True)
entries =query.fetch(1000)
db.delete(entries)
\# This could bulk delete 1000 entities a time
Update 2013-10-28:
remote_shell_api.py has been replaced by remote_api_shell.py, and you should connect with remote_api_shell.py -s your_app_id.appspot.com, according to the documentation.
There is a new experimental feature Datastore Admin, after enabling it in app settings, you can bulk delete as well as backup your datastore through the web ui.
The fastest and efficient way to handle bulk delete on Datastore is by using the new mapper API announced on the latest Google I/O.
If your language of choice is Python, you just have to register your mapper in a mapreduce.yaml file and define a function like this:
from mapreduce import operation as op
def process(entity):
yield op.db.Delete(entity)
On Java you should have a look to this article that suggests a function like this:
#Override
public void map(Key key, Entity value, Context context) {
log.info("Adding key to deletion pool: " + key);
DatastoreMutationPool mutationPool = this.getAppEngineContext(context)
.getMutationPool();
mutationPool.delete(value.getKey());
}
EDIT:
Since SDK 1.3.8, there's a Datastore admin feature for this purpose
You can clear the development server datastore when you run the server:
/path/to/dev_appserver.py --clear_datastore=yes myapp
You can also abbreviate --clear_datastore with -c.
If you have a significant amount of data, you need to use a script to delete it. You can use remote_api to clear the datastore from the client side in a straightforward manner, though.
Here you go: Go to Datastore Admin, and then select the Entity type you want to delete and click Delete. Mapreduce will take care of deleting!
There are several ways you can use to remove entries from App Engine's Datastore:
First, think whether you really need to remove entries. This is expensive and it might be cheaper to not remove them.
You can delete all entries by hand using the Datastore Admin.
You can use the Remote API and remove entries interactively.
You can remove the entries programmatically using a couple lines of code.
You can remove them in bulk using Task Queues and Cursors.
Or you can use Mapreduce to get something more robust and fancier.
Each one of these methods is explained in the following blog post:
http://www.shiftedup.com/2015/03/28/how-to-bulk-delete-entries-in-app-engine-datastore
Hope it helps!
The zero-setup way to do this is to send an execute-arbitrary-code HTTP request to the admin service that your running app already, automatically, has:
import urllib
import urllib2
urllib2.urlopen('http://localhost:8080/_ah/admin/interactive/execute',
data = urllib.urlencode({'code' : 'from google.appengine.ext import db\n' +
'db.delete(db.Query())'}))
Source
I got this from http://code.google.com/appengine/articles/remote_api.html.
Create the Interactive Console
First, you need to define an interactive appenginge console. So, create a file called appengine_console.py and enter this:
#!/usr/bin/python
import code
import getpass
import sys
# These are for my OSX installation. Change it to match your google_appengine paths. sys.path.append("/Applications/GoogleAppEngineLauncher.app/Contents/Resources/GoogleAppEngine-default.bundle/Contents/Resources/google_appengine")
sys.path.append("/Applications/GoogleAppEngineLauncher.app/Contents/Resources/GoogleAppEngine-default.bundle/Contents/Resources/google_appengine/lib/yaml/lib")
from google.appengine.ext.remote_api import remote_api_stub
from google.appengine.ext import db
def auth_func():
return raw_input('Username:'), getpass.getpass('Password:')
if len(sys.argv) < 2:
print "Usage: %s app_id [host]" % (sys.argv[0],)
app_id = sys.argv[1]
if len(sys.argv) > 2:
host = sys.argv[2]
else:
host = '%s.appspot.com' % app_id
remote_api_stub.ConfigureRemoteDatastore(app_id, '/remote_api', auth_func, host)
code.interact('App Engine interactive console for %s' % (app_id,), None, locals())
Create the Mapper base class
Once that's in place, create this Mapper class. I just created a new file called utils.py and threw this:
class Mapper(object):
# Subclasses should replace this with a model class (eg, model.Person).
KIND = None
# Subclasses can replace this with a list of (property, value) tuples to filter by.
FILTERS = []
def map(self, entity):
"""Updates a single entity.
Implementers should return a tuple containing two iterables (to_update, to_delete).
"""
return ([], [])
def get_query(self):
"""Returns a query over the specified kind, with any appropriate filters applied."""
q = self.KIND.all()
for prop, value in self.FILTERS:
q.filter("%s =" % prop, value)
q.order("__key__")
return q
def run(self, batch_size=100):
"""Executes the map procedure over all matching entities."""
q = self.get_query()
entities = q.fetch(batch_size)
while entities:
to_put = []
to_delete = []
for entity in entities:
map_updates, map_deletes = self.map(entity)
to_put.extend(map_updates)
to_delete.extend(map_deletes)
if to_put:
db.put(to_put)
if to_delete:
db.delete(to_delete)
q = self.get_query()
q.filter("__key__ >", entities[-1].key())
entities = q.fetch(batch_size)
Mapper is supposed to be just an abstract class that allows you to iterate over every entity of a given kind, be it to extract their data, or to modify them and store the updated entities back to the datastore.
Run with it!
Now, start your appengine interactive console:
$python appengine_console.py <app_id_here>
That should start the interactive console. In it create a subclass of Model:
from utils import Mapper
# import your model class here
class MyModelDeleter(Mapper):
KIND = <model_name_here>
def map(self, entity):
return ([], [entity])
And, finally, run it (from you interactive console):
mapper = MyModelDeleter()
mapper.run()
That's it!
You can do it using the web interface. Login into your account, navigate with links on the left hand side. In Data Store management you have options to modify and delete data. Use respective options.
I've created an add-in panel that can be used with your deployed App Engine apps. It lists the kinds that are present in the datastore in a dropdown, and you can click a button to schedule "tasks" that delete all entities of a specific kind or simply everything. You can download it here:
http://code.google.com/p/jobfeed/wiki/Nuke
For Python, 1.3.8 includes an experimental admin built-in for this. They say: "enable the following builtin in your app.yaml file:"
builtins:
- datastore_admin: on
"Datastore delete is currently available only with the Python runtime. Java applications, however, can still take advantage of this feature by creating a non-default Python application version that enables Datastore Admin in the app.yaml. Native support for Java will be included in an upcoming release."
Open "Datastore Admin" for your application and enable Admin. Then all of your entities will be listed with check boxes. You can simply select the unwanted entites and delete them.
This is what you're looking for...
db.delete(Entry.all(keys_only=True))
Running a keys-only query is much faster than a full fetch, and your quota will take a smaller hit because keys-only queries are considered small ops.
Here's a link to an answer from Nick Johnson describing it further.
Below is an end-to-end REST API solution to truncating a table...
I setup a REST API to handle database transactions where routes are directly mapped through to the proper model/action. This can be called by entering the right url (example.com/inventory/truncate) and logging in.
Here's the route:
Route('/inventory/truncate', DataHandler, defaults={'_model':'Inventory', '_action':'truncate'})
Here's the handler:
class DataHandler(webapp2.RequestHandler):
#basic_auth
def delete(self, **defaults):
model = defaults.get('_model')
action = defaults.get('_action')
module = __import__('api.models', fromlist=[model])
model_instance = getattr(module, model)()
result = getattr(model_instance, action)()
It starts by loading the model dynamically (ie Inventory found under api.models), then calls the correct method (Inventory.truncate()) as specified in the action parameter.
The #basic_auth is a decorator/wrapper that provides authentication for sensitive operations (ie POST/DELETE). There's also an oAuth decorator available if you're concerned about security.
Finally, the action is called:
def truncate(self):
db.delete(Inventory.all(keys_only=True))
It looks like magic but it's actually very straightforward. The best part is, delete() can be re-used to handle deleting one-or-many results by adding another action to the model.
You can Delete All Datastore by deleting all Kinds One by One.
with google appengine dash board. Please follow these Steps.
Login to https://console.cloud.google.com/datastore/settings
Click Open Datastore Admin. (Enable it if not enabled.)
Select all Entities and press delete.(This Step run a map reduce job for deleting all selected Kinds.)
for more information see This image http://storage.googleapis.com/bnifsc/Screenshot%20from%202015-01-31%2023%3A58%3A41.png
If you have a lot of data, using the web interface could be time consuming. The App Engine Launcher utility lets you delete everything in one go with the 'Clear datastore on launch' checkbox. This utility is now available for both Windows and Mac (Python framework).
For the development server, instead of running the server through the google app engine launcher, you can run it from the terminal like:
dev_appserver.py --port=[portnumber] --clear_datastore=yes [nameofapplication]
ex: my application "reader" runs on port 15080. After modify the code and restart the server, I just run "dev_appserver.py --port=15080 --clear_datastore=yes reader".
It's good for me.
Adding answer about recent developments.
Google recently added datastore admin feature. You can backup, delete or copy your entities to another app using this console.
https://developers.google.com/appengine/docs/adminconsole/datastoreadmin#Deleting_Entities_in_Bulk
I often don't want to delete all the data store so I pull a clean copy of /war/WEB-INF/local_db.bin out source control. It may just be me but it seems even with the Dev Mode stopped I have to physically remove the file before pulling it. This is on Windows using the subversion plugin for Eclipse.
PHP variation:
import com.google.appengine.api.datastore.Query;
import com.google.appengine.api.datastore.DatastoreServiceFactory;
define('DATASTORE_SERVICE', DatastoreServiceFactory::getDatastoreService());
function get_all($kind) {
$query = new Query($kind);
$prepared = DATASTORE_SERVICE->prepare($query);
return $prepared->asIterable();
}
function delete_all($kind, $amount = 0) {
if ($entities = get_all($kind)) {
$r = $t = 0;
$delete = array();
foreach ($entities as $entity) {
if ($r < 500) {
$delete[] = $entity->getKey();
} else {
DATASTORE_SERVICE->delete($delete);
$delete = array();
$r = -1;
}
$r++; $t++;
if ($amount && $amount < $t) break;
}
if ($delete) {
DATASTORE_SERVICE->delete($delete);
}
}
}
Yes it will take time and 30 sec. is a limit. I'm thinking to put an ajax app sample to automate beyond 30 sec.
for amodel in db.Model.__subclasses__():
dela=[]
print amodel
try:
m = amodel()
mq = m.all()
print mq.count()
for mw in mq:
dela.append(mw)
db.delete(dela)
#~ print len(dela)
except:
pass
If you're using ndb, the method that worked for me for clearing the datastore:
ndb.delete_multi(ndb.Query(default_options=ndb.QueryOptions(keys_only=True)))
For any datastore that's on app engine, rather than local, you can use the new Datastore API. Here's a primer for how to get started.
I wrote a script that deletes all non-built in entities. The API is changing pretty rapidly, so for reference, I cloned it at commit 990ab5c7f2063e8147bcc56ee222836fd3d6e15b
from gcloud import datastore
from gcloud.datastore import SCOPE
from gcloud.datastore.connection import Connection
from gcloud.datastore import query
from oauth2client import client
def get_connection():
client_email = 'XXXXXXXX#developer.gserviceaccount.com'
private_key_string = open('/path/to/yourfile.p12', 'rb').read()
svc_account_credentials = client.SignedJwtAssertionCredentials(
service_account_name=client_email,
private_key=private_key_string,
scope=SCOPE)
return Connection(credentials=svc_account_credentials)
def connect_to_dataset(dataset_id):
connection = get_connection()
datastore.set_default_connection(connection)
datastore.set_default_dataset_id(dataset_id)
if __name__ == "__main__":
connect_to_dataset(DATASET_NAME)
gae_entity_query = query.Query()
gae_entity_query.keys_only()
for entity in gae_entity_query.fetch():
if entity.kind[0] != '_':
print entity.kind
entity.key.delete()
continuing the idea of svpino it is wisdom to reuse records marked as delete. (his idea was not to remove, but mark as "deleted" unused records). little bit of cache/memcache to handle working copy and write only difference of states (before and after desired task) to datastore will make it better. for big tasks it is possible to write itermediate difference chunks to datastore to avoid data loss if memcache disappeared. to make it loss-proof it is possible to check integrity/existence of memcached results and restart task (or required part) to repeat missing computations. when data difference is written to datastore, required computations are discarded in queue.
other idea similar to map reduced is to shard entity kind to several different entity kinds, so it will be collected together and visible as single entity kind to final user. entries are only marked as "deleted". when "deleted" entries amount per shard overcomes some limit, "alive" entries are distributed between other shards, and this shard is closed forever and then deleted manually from dev console (guess at less cost) upd: seems no drop table at console, only delete record-by-record at regular price.
it is possible to delete by query by chunks large set of records without gae failing (at least works locally) with possibility to continue in next attempt when time is over:
qdelete.getFetchPlan().setFetchSize(100);
while (true)
{
long result = qdelete.deletePersistentAll(candidates);
LOG.log(Level.INFO, String.format("deleted: %d", result));
if (result <= 0)
break;
}
also sometimes it useful to make additional field in primary table instead of putting candidates (related records) into separate table. and yes, field may be unindexed/serialized array with little computation cost.
For all people that need a quick solution for the dev server (as time of writing in Feb. 2016):
Stop the dev server.
Delete the target directory.
Rebuild the project.
This will wipe all data from the datastore.
I was so frustrated about existing solutions for deleting all data in the live datastore that I created a small GAE app that can delete quite some amount of data within its 30 seconds.
How to install etc: https://github.com/xamde/xydra
For java
DatastoreService db = DatastoreServiceFactory.getDatastoreService();
List<Key> keys = new ArrayList<Key>();
for(Entity e : db.prepare(new Query().setKeysOnly()).asIterable())
keys.add(e.getKey());
db.delete(keys);
Works well in Development Server
You have 2 simple ways,
#1: To save cost, delete the entire project
#2: using ts-datastore-orm:
https://www.npmjs.com/package/ts-datastore-orm
await Entity.truncate();
The truncate can delete around 1K rows per seconds
Here's how I did this naively from a vanilla Google Cloud Shell (no GAE) with python3:
from google.cloud import datastore
client = datastore.Client()
query.keys_only()
for counter, entity in enumerate(query.fetch()):
if entity.kind.startswith('_'): # skip reserved kinds
continue
print(f"{counter}: {entity.key}")
client.delete(entity.key)
This takes a very long time even with a relatively small amount of keys but it works.
More info about the Python client library: https://googleapis.dev/python/datastore/latest/client.html
As of 2022, there are two ways to delete a kind from a (largeish) datastore to the best of my knowledge. Google recommends using a Dataflow template. The template will basically pull each entity one by one subject to a GQL query, and then delete it. Interestingly, if you are deleting a large number of rows (> 10m), you will run into datastore troubles; as it will fail to provide enough capacity, and your operations to the datastore will start timing out. However, only the kind you are mass deleting from will be effected.
If you have less than 10m rows, you can just use this go script:
import (
"cloud.google.com/go/datastore"
"context"
"fmt"
"google.golang.org/api/option"
"log"
"strings"
"sync"
"time"
)
const (
batchSize = 10000 // number of keys to get in a single batch
deleteBatchSize = 500 // number of keys to delete in a single batch
projectID = "name-of-your-GCP-project"
serviceAccount = "path-to-sa-file"
table = "kind-to-delete"
)
func min(a, b int) int {
if a < b {
return a
}
return b
}
func deleteBatch(table string) int {
ctx := context.Background()
client, err := datastore.NewClient(ctx, projectID, option.WithCredentialsFile(serviceAccount))
if err != nil {
log.Fatalf("Failed to open client: %v", err)
}
defer client.Close()
query := datastore.NewQuery(table).KeysOnly().Limit(batchSize)
keys, err := client.GetAll(ctx, query, nil)
if err != nil {
fmt.Printf("%s Failed to get %d keys : %v\n", table, batchSize, err)
return -1
}
var wg sync.WaitGroup
for i := 0; i < len(keys); i += deleteBatchSize {
wg.Add(1)
go func(i int) {
batch := keys[i : i+min(len(keys)-i, deleteBatchSize)]
if err := client.DeleteMulti(ctx, batch); err != nil {
// not a big problem, we'll get them next time ;)
fmt.Printf("%s Failed to delete multi: %v", table, err)
}
wg.Done()
}(i)
}
wg.Wait()
return len(keys)
}
func main() {
var globalStartTime = time.Now()
fmt.Printf("Deleting \033[1m%s\033[0m\n", table)
for {
startTime := time.Now()
count := deleteBatch(table)
if count >= 0 {
rate := float64(count) / time.Since(startTime).Seconds()
fmt.Printf("Deleted %d keys from %s in %.2fs, rate %.2f keys/s\n", count, table, time.Since(startTime).Seconds(), rate)
if count == 0 {
fmt.Printf("%s is now clear.\n", table)
break
}
} else {
fmt.Printf("Retrying after short cooldown\n")
time.Sleep(10 * time.Second)
}
}
fmt.Printf("Total time taken %s.\n", time.Since(globalStartTime))
}

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