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dwh-mixpanel
Advanced tools
Stream queries from your data warehouse to events, profiles, groups, or lookup tables in Mixpanel... rETL style 💫.
No intermediate staging/storage required.
Supported Data Warehouses:
run the module, and provide a configuration file as the first argument:
npx dwh-mixpanel ./myConfig.json
for help building a configuration file, run the module with no arguments:
npx dwh-mixpanel
what next?
dwh-mixpanel
as a moduleas stated in the tldr, if you run dwh-mixpanel
with no arguments you get a CLI which helps you build a configuration file:
npx dwh-mixpanel
it looks like this:
at the end of this walkthrough, a JSON file will be saved to your current working directory; this JSON will contain the configuration of what you typed into the CLI. the CLI will then ask you if you'd like to trigger a run:
once you have a configuration file, you can run (and re-run) that job by passing the configuration file as the first argument to this module:
npx dwh-mixpanel snowflake-mixpanel.json
as it runs, you'll get some console output as to the status of your job:
once the pipeline is complete, it will stash logs in the current working directory, and you can see your data in mixpanel!
note: if you will use this module frequently, consider a global install:
npm install --global dwh-mixpanel
and then you don't need the npx
:
dwh-mixpanel ./myConfig.json
dwh-mixpanel
can also be used as a ESM module inside any node.js environment. this is useful for automated cloud ingestion pipelines and scheduled syncs with your warehouse.
install it from npm
:
npm install dwh-mixpanel
and then you use it as you would any other dependency:
import dwhMp from "dwh-mixpanel";
dwh-mixpanel
exports a single function, which takes in a single parameter - a configuration object.
this is the entry-point for the whole module:
const myConfig = {
dwh: "bigquery",
sql: "SELECT * FROM EVENTS",
//etc...
};
const bqToMpSummary = await dwhMp(myConfig);
the module returns a summary
of the entire pipeline, with statistics and logs about how many records were processed, throughput, and metadata from the warehouse.
{
mixpanel: {
success: 100000,
failed: 0,
total: 100000,
requests: 50,
recordType: "event",
duration: 15314,
human: "15.314 seconds",
retries: 0,
version: "2.2.287",
workers: 10,
eps: 6529,
rps: 3.265,
responses: [],
errors: [],
},
bigquery: {
job: {
//job infos
},
metadata: {
//query metadata
},
schema: {
//schema
}
}
}
your configuration is an object (or JSON) with the following structure:
{
dwh: "", // warehouse name
auth: {}, // warehouse auth details
sql: "", // a SQL query
mappings: {}, // col headers → mixpanel fields
mixpanel: {}, // mixpanel auth
options: {}, // job options
tags: {} // arbitrary tags
}
you can find examples in the repo for different warehouses. additionally, the module is typed using jsdoc, so you should have a good experience using it in your IDE:
here's a description of each of those keys (and values) mean
a string representing the data warehouse you're connecting too.
bigquery
, athena
, snowflake
, azure
, salesforce
an object {}
containing the service account/credentials to use when authenticating with the data warehouse.
each cloud warehouse has its own method(s) of authenticating API calls, which usually consist of a username and a password, secret, or private key.
to read more about the ways you can authenticate with a supported data warehouse, see warehouse details
a valid SQL Query to run (as a job) in your data warehouse; this is the "model" for the data that will be sent to mixpanel. your SQL query will usually be in the form of a SELECT {fields}
or SELECT *
statement:
SELECT
eventName,
user_id,
timestamp,
prop_a,
prop_b,
prop_c,
rowId as insert_id
FROM
"myProject.myDB.myTable"
WHERE
env is "prod"
your SQL query should produce a flat, non-nested table that has the fields and records you wish to stream to mixpanel. your column headers can have any title; you will provide a mappings dictionary (detailed below) to describe how mixpanel should receive the fields.
note: most field labels can be retitled post-ingestion using lexicon, mixpanel's data governance suite.
an object {}
containing mapping assignments of COLUMN headers in the warehouse table to JSON property keys in mixpanel's data model.
providing mappings is not a tedious task; mixpanel is a schemaless tool designed for semi-structured data, so any column not explicitly mapped which is present in the table will become an event/user property key and value.
therefore, your SQL query should select all the fields you want in mixpanel, and the only fields you must provide mappings for depend on the required fields for the type of data you're importing:
event mappings:
{
// REQUIRED
'event_name_col': '', // column for event name
'distinct_id_col': '', // column for uniquer user id
'time_col': '', // column for event time
// OPTIONAL
'insert_id_col': '' // column for row id (deduplication)
}
note: insert_id_col
is required when using strict
mode
user or group profiles mappings:
{
// REQUIRED
'distinct_id_col': '', // column for uniquer user id
// OPTIONAL
'profileOperation': '', // the $set style operation to use
'name_col': '', // column $name to use for the user/group profile
'email_col': '', // column $email to use for the user/group profile
'avatar_col': '', // column $email to use for the user/group profile
'created_col': '', // column $created (timestamp) to use
'phone_col': '', // column $phone to use for the user/group profile
'latitude_col': '', // column $latitude to use for the user/group profile
'longitude_col': '', // column $longitude to use for the user/group profile
'ip_co': '' // column $ip to use for the user/group profile
}
lookup tables mappings:
{
// REQUIRED
'lookup_col' : '' //the "join" column for the lookup table
//hint: ^ this is usually the first column in the table
}
the key to remember about mappings
is that you a giving the module a guide to understand how to map fields from your warehouse to required fields for the different mixpanel data types.
here's an example:
SELECT
insert_id, timestamp, action, uuid, theme, class
FROM
mydnd.campaign.db
which produces this table:
insert_id | timestamp | action | uuid | theme | class |
---|---|---|---|---|---|
abc-123 | 4:19 PM | attack | ak | dark | cleric |
xyz-345 | 4:20 PM | defend | alice | light | bard |
cba-678 | 4:20 PM | attack | bob | light | paladin |
zyx-901 | 4:21 PM | sneak | eve | dark | rogue |
with this mapping:
{
event_name_col: 'action',
distinct_id_col: 'uuid',
time_col: 'timestamp',
insert_id_col: 'insert_id'
}
then produces these events in mixpanel:
[
{
event: "attack",
properties: {
distinct_id: "ak",
time: 1234567890,
$insert_id: "abc-123",
theme: "dark",
class: "cleric",
},
},
{
event: "defend",
properties: {
distinct_id: "alice",
time: 1234577891,
$insert_id: "xyz-345",
theme: "light",
class: "bard",
},
},
//etc...
];
for more info on mixpanel's data structure, see this deep-dive
an object {}
containing authentication details used to connect to your mixpanel project.
{
project_id: '', //your mixpanel project id
type: 'event', //type of record to import
region: 'US', //or EU
//one of service details OR api secret is required
service_account: '', //service account user name
service_secret: '', //service account secret
api_secret: '', //project api secret [deprecated]
//required for profiles
token: '', //mixpanel project token
//required for groups
groupKey: '', //the group key for this group
//required for lookup tables
lookupTableId: '' //the lookup table to replace
}
note: you can find most of these values in the your mixpanel project's settings
an object {}
containing various options for the job.
{
logFile: 'myLog.txt', // local path to write log files to
verbose: true, // display verbose console output
strict: false, // use strict mode when sending data to mixpanel
compress: false, // gzip data before egress
workers: 20 // number of concurrent workers to make requests to mixpanel
}
the workers
option is important because it governs concurrency, which can greatly affect throughput. best results are observed between 10-20 workers.
an object {}
containing arbitrary key:value
string pairs that will be used to tag the data. this is particularly useful if this module is being used as part of an automated pipeline, and you wish to tag the data with runIds
or some other reference value.
{
mixpanel: {
type: "event"
},
tags: {
"foo": "bar"
// every event in mixpanel will have a {foo: 'bar'} prop
}
}
this works on all record types:
{
mixpanel: {
type: "user"
},
tags: {
"baz": "qux"
// every user profile updated will have a {baz: 'qux'} prop
}
}
the data warehouse connectors used by this module are implemented as middleware, and therefore they have authentication strategies with different field requirements.
in most cases, dwh-mixpanel
wraps the vendor SDKs of each warehouse with it's own API, so when passing auth
params in your configuration, you can use any values that are supported by your warehouse, provided those credentials have the appropriate permissions.
below are details for authentication strategies and permissions required for in each supported warehouse. if you find an auth method or strategy that you need and is not supported for your warehouse, please file an issue
most bigquery jobs will be authenticated with GCP service accounts
the service account will need the following permissions in bigquery AND on the specific dataset being queried:
bigquery.jobs.create
bigquery.jobs.get
bigquery.datasets.get
bigquery.tables.get
bigquery.tables.getData
in my experience, the data viewer
+ bigquery job user
roles set together satisfies these cases; if a required permission is missing, the output will tell you what it is.
the typical fields used for auth are project_id
, private_key
, and client_email
; location
will need to be added manually based on the region of your bigquery instance:
{
dwh: "bigquery",
auth : {
"project_id": "my-gcp-project", //GCP project
"client_email": "serviceAccount@email.com", //service acct email
"private_key": "-----BEGIN PRIVATE KEY-----\n...\n-----END PRIVATE KEY-----\n", // service account private key
"location": "US" //bigquery location.. this is required!
}
}
in most cases, you can drop your exported JSON keys into the auth
param, and it will work. here's a video where i go through the service account setup, start to finish.
if you are running dwh-mixpanel
from your local, and you do not have IAM access in GCP to create service accounts, but you do have user-level access to the datasets in BigQuery, you can use Application Default Credentials (ADC) which leverage your local GCP account to authenticate with bigQuery's APIs.
the general steps here are:
gcloud
CLI and initialize itgcloud init
gcloud auth application-default login
auth
param to an empty object {}
{
"dwh": "bigquery",
"auth": {},
"sql": "SELECT * FROM FOO"
}
dwh-mixpanel
with your updated configuration file:npx dwh-mixpanel ./bigquery-mixpanel
snowflake jobs with authenticate with a user name + password.
the fields used for auth are account
identifier , username
, and password
; you will also need to provide your warehouse
name, database
name, and table schema
. most of these values can be found in the UI or the SQL console.
{
dwh: "snowflake",
auth : {
"account": "foobar.us-central1.gcp", // your snowflake identifier
"username": "",
"password": "",
"database": "PROD1", // database to use
"schema": "PUBLIC", // schema to use
"warehouse": "COMPUTE_WH" //warehouse to use
}
}
no special permissions are required for snowflake - only that the user/pass you entered can view and query the dataset.
note: 2FA with Snowflake is not currently supported in this module.
to query athena from this module, your user account (or service account) will need permission to take the following actions in athena:
since athena depends on S3, your account will also need access to the following actions in S3:
the S3 bucket you assign permissions to should be the same one athena uses for storage; you can see this in the athena UI:
note: all queries made to athena are stored as CSV files in S3; this module uses the DeleteObject
action to delete the materialized CSV after the data is imported into mixpanel.
most AWS accounts can be setup for programmatic access using an accessKeyId
and a secretAccessKey
; you'll also need to add the region
of your S3 instance.
{
dwh: "athena",
auth : {
"accessKeyId": "",
"secretAccessKey": "",
"region": "us-east-2" //note this is important!
}
}
Azure SQL (managed + on premise) servers employ usernames and passwords for authentication; there are no special permissions required... the user you authenticate as should have permissions to run the query.
there are two common patterns for entering credentials, connection strings and JSON ... they are essentially the same thing in different formats:
Server=tcp:my-sql-server.database.windows.net,1433;Database=database;User Id=username;Password=password;Encrypt=true
Driver=msnodesqlv8;Server=(local)\INSTANCE;Database=database;UID=DOMAIN\username;PWD=password;Encrypt=true
you can input your connection string into the auth
object with the key connection_string
:
{
dwh: "azure",
auth: {
connection_string: "my-sql-server.database.windows.net,1433; etc..."
}
}
if your database is hosted in Azure Cloud, you can find your connection strings in the Azure SQL UI; this module uses the ADO.NET syntax:
make sure to choose the right connection string version that is supported by your database. (hint: not all Azure DBs are setup with Active Directory)
if you wish, you may also pass your credentials as JSON; the parameters are very similar to what's encoded in the connection string. they look like this:
{
dwh: "azure",
auth: {
user: "",
password: "",
server: "",
port: 1433, //default
domain: "",
database: ""
}
}
you can also pass other pool configuration options to the auth
object... see the full list of params
while salesforce may not typically be thought of as a "data warehouse" (great for transactions; not so great for analysis), it can be queried with SQL. salesforce uses SOQL, a variant of SQL for sObjects.
therefore, you can model events, profiles, groups or lookup tables as SOQL queries, and pipe them directly to mixpanel!
the data model for salesforce is quite unique, and therefore this module works differently when interfacing with salesforce than it does with other warehouses.
for authentication you need only add a username
and password
for the auth
object:
{
dwh: "salesforce",
auth: {
user: "", //your username
password: "", // your password + security token
version: "51.0" // API version to use; 51 is default
}
}
dwh-mixpanel
uses salesforce's SOAP login API for authentication... this means your password
is your normal salesforce password with a concatenated security token. if your UI password was: foo
and your security token was bar-bazqux
your API password is foobar-bazqux
if you do not have a security token, here are the steps to reset it
this module provides additional options which govern the transformation of salesforce records into usable mixpanel entities; these options are all turned on by default and can be changed in the auth
section of the configuration file if desired:
{
dwh: "salesforce",
auth: {
user,
password,
"resolve_field_names": true, // "Renewal_Date__c" → "Contract Renewal Date"
"rename_primary_id" : true, // "Id" → "Account.Id"
"add_sfdc_links": true // add salesforce URLs to all records
}
}
resolve_field_names
with this option, dwh-mixpanel
will query your salesforce objects' schema to transform the API fields (Renewal_Date__c
) into human readable labels (Contract Renewal Date
) which will be sent in mixpanel
rename_primary_id
this option will turn the Id
column header into sObject.Id
; you can still reference it as sObject.Id
or Id
in your configuration file's mappings. SOQL queries of the form SELECT Id ... FROM sObject
have a generic Id
column can be a pain-point when joining records from different objects.
add_sfdc_links
this option adds a salesforce link
property to each mixpanel record, so you can easily jump from mixpanel to salesforce in one click!
for user profiles, group profiles, and lookup tables, you must provide column mappings to mixpanel objects. relationship fields using the dot .
syntax allow you to traverse objects, and are easy to reference:
for example:
SELECT
Account.Id,
Account.Name,
Account.Owner.Name, -- relationships
Account.CSM__c.Name,
Account.ARR__c,
Account.NPS__c,
Account.plan_type__c.monthly_spend__c -- custom fields
FROM
Account
would (likely) use the following mappings:
{
dwh: "salesforce",
mappings: {
distinct_id_col: "Account.Id",
name_col: "Account.Name",
email_col: "Account.Owner.Name",
},
mixpanel: {
type : "group",
groupKey: "Account.Id" //important!
}
}
this will produce group profiles for every account, using each account's Id
as the $group_id
modeling events from salesforce in mixpanel is a bit different; in most cases, you will want to model field history objects as events in mixpanel. these objects contain the "change tables" that describe the lifecycle of a salesforce object... when an object is created, or when it's field value change (i.e. an Opportunity
changing Stage
), it's field history is updated..
to properly use this module, every SOQL query modeling history MUST contain the fields:
Field, NewValue, OldValue, CreatedDate
these fields are used internally to determine the event name, event time, and $insert_id therefore, any mappings supplied to event_name_col
, time_col
, or insert_id_col
will be ignored.
you will need to supply a mapping for distinct_id_col
(usually the Id
of the primary object being queried)
for example, we might query the OpportunityFieldHistory
to get events for each "field change" on each opportunity:
SELECT
Id, DataType, Field, NewValue, OldValue, CreatedDate,
Opportunity.Id, Opportunity.Name, Opportunity.Amount,
Opportunity.Owner.Name, Opportunity.Account.Name
FROM
OpportunityFieldHistory
and we might use the following mapping:
{
dwh: "salesforce",
mappings: {
event_name_col: "", // ignored!
insert_id_col: "", // ignored!
time_col: "", // ignored!
distinct_id_col: "Opportunity.Id", //important!
},
mixpanel: {
type : "event"
}
}
this would model all field changes to any opportunities as events in mixpanel, using the opportunity's Id
as the distinct_id
in mixpanel.
you can also model events that do not contain history tables; keep in mind that you'll need to choose a time_col
mapping, (usually CreatedDate
or LastModifiedDate
) which determine when the event occurred.
in these cases, you are effectively modeling and event which describes when a particular salesforce object was created or modified, but keep in mind that your field values always contain the most current version of that object's properties, not the values at the time the object was created.
this is still quote useful, since some many salesforce objects are created once and never modified; for example, we might model new Tasks
or Calls
as the following:
-- modeling Tasks object as events
SELECT
Id, Who.Id, Who.Name, Who.RecordType.SobjectType,
What.Id, What.Name, What.RecordType.SobjectType,
AccountId, CreatedDate, CreatedBy.Id, CreatedBy.Name
FROM
Task
WHERE
LastModifiedDate = Today
we need supply the time_col
, insert_id_col
, and distinct_id_col
:
{
dwh: "salesforce",
mappings: {
event_name_col: "", // optional!
insert_id_col: "Id", // important!
time_col: "CreatedDate", //important!
distinct_id_col: "Who.Id", //important!
},
mixpanel: {
type : "event"
}
}
the event_name_col
is optional; if it is supplied, that will be a hardcoded event name in mixpanel:
{
mappings: {
event_name_col: "task was created!"
}
}
would produce:
{
event: "task was created!",
properties: {}
}
if event_name_col
is not supplied, event names will be created automatically based on the sObject
that is being queried (in this case task
).
note: nested SOQL subqueries are not currently supported for salesforce rETLs.
if you would prefer to store your authentication details as environment variables or in an .env
file, you may do so.
this module will find those values provided they are correctly named.
here is a sample of how environment variables can be used for mixpanel:
MP_SERVICE_ACCOUNT=myServiceAcct
MP_SERVICE_SECRET=myServiceSecret
MP_API_SECRET=myAPISecret
MP_TOKEN=myToken
MP_LOOKUP_TABLE=myLookupTableId
for the warehouse auth, use the key DWH_AUTH
and for the value use stringified JSON that you would pass to auth
in the configuration file:
DWH_AUTH='{
"project_id": "ak-internal-tool-1613096051700",
"private_key": "-----BEGIN PRIVATE KEY-----\n...\n-----END PRIVATE KEY-----\n",
"client_email": "mySerAcct@iam.google.com",
"location": "US"
}'
that's it for now. have fun!
FAQs
rETL from a data warehouse to mixpanel
The npm package dwh-mixpanel receives a total of 1 weekly downloads. As such, dwh-mixpanel popularity was classified as not popular.
We found that dwh-mixpanel demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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