Introduction
This is the second article of the series "Learn MongoDB with me". If you haven't read my previous post on this topic, I strongly recommend you to find it here. This is the continuation of exploring the Mongo shells, we will be performing some commands on the Mongo shells. For easy reference, I will try to add screenshots for each step I am following. I hope it will help you come along with me. Thanks for reading.
Background
Like I said, it is going to be the second part of the series. I believe that you have enough knowledge about Mongo DB and how to set up it? How a Mongo shell can be used? If you are not able to answer these questions yourself, please consider reading my previous post again.
Mongo Shells, the Perfect CLI
We can do anything in the Mongo shell, to make the statement clear. I am going to perform some CRUD operations (Create, Read, Update, Delete) within Mongo shells. To do so, we can use Mongo import commands. The Mongo import commands can do the work for you, even if the data is in .tsv, .csv, .json, etc. Let's see those in action.
As a first step, let us see some documentation.
C:\Program Files\MongoDB\Server\3.4\bin>mongoimport --help
The above command will give you all the options available to get started.
Usage:
mongoimport <options> <file>
Import CSV, TSV or JSON data into MongoDB. If no file is provided, mongoimport reads from stdin.
See http://docs.mongodb.org/manual/reference/program/mongoimport/ for more information.
general options:
/help print usage
/version print the tool version and
exit
verbosity options:
/v, /verbose:<level> more detailed log output
(include multiple times for
more verbosity, e.g. -vvvvv,
or specify a numeric value,
e.g. --verbose=N)
/quiet hide all log output
connection options:
/h, /host:<hostname> mongodb host to connect to
(setname/host1,host2 for
replica sets)
/port:<port> server port (can also use
--host hostname:port)
kerberos options:
/gssapiServiceName:<service-name> service name to use when
authenticating using
GSSAPI/Kerberos ('mongodb' by
default)
/gssapiHostName:<host-name> hostname to use when
authenticating using
GSSAPI/Kerberos (remote
server's address by default)
ssl options:
/ssl connect to a mongod or mongos
that has ssl enabled
/sslCAFile:<filename> the .pem file containing the
root certificate chain from
the certificate authority
/sslPEMKeyFile:<filename> the .pem file containing the
certificate and key
/sslPEMKeyPassword:<password> the password to decrypt the
sslPEMKeyFile, if necessary
/sslCRLFile:<filename> the .pem file containing the
certificate revocation list
/sslAllowInvalidCertificates bypass the validation for
server certificates
/sslAllowInvalidHostnames bypass the validation for
server name
/sslFIPSMode use FIPS mode of the
installed openssl library
authentication options:
/u, /username:<username> username for authentication
/p, /password:<password> password for authentication
/authenticationDatabase:<database-name> database that holds the
user's credentials
/authenticationMechanism:<mechanism> authentication mechanism to
use
namespace options:
/d, /db:<database-name> database to use
/c, /collection:<collection-name> collection to use
uri options:
/uri:mongodb-uri mongodb uri connection string
input options:
/f, /fields:<field>[,<field>]* comma separated list of
fields, e.g. -f name,age
/fieldFile:<filename> file with field names - 1 per
line
/file:<filename> file to import from; if not
specified, stdin is used
/headerline use first line in input
source as the field list (CSV
and TSV only)
/jsonArray treat input source as a JSON
array
/parseGrace:<grace> controls behavior when type
coercion fails - one of:
autoCast, skipField, skipRow,
stop (defaults to 'stop')
(default: stop)
/type:<type> input format to import: json,
csv, or tsv (defaults to
'json') (default: json)
/columnsHaveTypes indicated that the field list
(from --fields, --fieldsFile,
or --headerline) specifies
types; They must be in the
form of
'<colName>.<type>(<arg>)'.
The type can be one of: auto,
binary, bool, date, date_go,
date_ms, date_oracle, double,
int32, int64, string. For
each of the date types, the
argument is a datetime layout
string. For the binary type,
the argument can be one of:
base32, base64, hex. All
other types take an empty
argument. Only valid for CSV
and TSV imports. e.g.
zipcode.string(),
thumbnail.binary(base64)
ingest options:
/drop drop collection before
inserting documents
/ignoreBlanks ignore fields with empty
values in CSV and TSV
/maintainInsertionOrder insert documents in the order
of their appearance in the
input source
/j, /numInsertionWorkers:<number> number of insert operations
to run concurrently (defaults
to 1) (default: 1)
/stopOnError stop importing at first
insert/upsert error
/mode:[insert|upsert|merge] insert: insert only. upsert:
insert or replace existing
documents. merge: insert or
modify existing documents.
defaults to insert
/upsertFields:<field>[,<field>]* comma-separated fields for
the query part when --mode is
set to upsert or merge
/writeConcern:<write-concern-specifier> write concern options e.g.
--writeConcern majority,
--writeConcern '{w: 3,
wtimeout: 500, fsync: true,
j: true}'
/bypassDocumentValidation bypass document validation
Insert Data to MondoDB using Mongo Shell
Now let's say I have the following JSON data, and we are going to insert the same to our db collection.
[
{
"color": "black",
"category": "hue",
"type": "primary",
"code": {
"rgba": [255,255,255,1],
"hex": "#000"
}
},
{
"color": "white",
"category": "value",
"code": {
"rgba": [0,0,0,1],
"hex": "#FFF"
}
},
{
"color": "red",
"category": "hue",
"type": "primary",
"code": {
"rgba": [255,0,0,1],
"hex": "#FF0"
}
},
{
"color": "blue",
"category": "hue",
"type": "primary",
"code": {
"rgba": [0,0,255,1],
"hex": "#00F"
}
},
{
"color": "yellow",
"category": "hue",
"type": "primary",
"code": {
"rgba": [255,255,0,1],
"hex": "#FF0"
}
},
{
"color": "green",
"category": "hue",
"type": "secondary",
"code": {
"rgba": [0,255,0,1],
"hex": "#0F0"
}
}
]
To do so, we need to use the following command:
C:\Program Files\MongoDB\Server\3.4\bin>mongoimport --db mylearning
--collection colors --jsonArray --file colors.json
Here, as you can see, we are providing the db name, collection, name, what is the data type of the file and finally the file name.
If you ever get the error as "Failed: open colors.json: The system cannot find the file specified.", please make sure that the document is in the server folder, in my case it is "C:\Program Files\MongoDB\Server\3.4\bin". If everything is fine, you will be able to see an output as follows:
C:\Program Files\MongoDB\Server\3.4\bin>mongoimport --db mylearning --collection colors
--jsonArray --file colors.json
2018-03-01T16:35:35.470+0530 connected to: localhost
2018-03-01T16:35:36.012+0530 imported 6 documents
C:\Program Files\MongoDB\Server\3.4\bin>
Reading the Data from a Collection in MongoDB
Now that we have colors collection, let's go and check whether the database has the data we are expecting.
C:\Program Files\MongoDB\Server\3.4\bin>mongo
MongoDB shell version v3.4.9
connecting to: mongodb://127.0.0.1:27017
MongoDB server version: 3.4.9
Server has startup warnings:
2018-03-01T16:24:43.793+0530 I CONTROL [initandlisten]
2018-03-01T16:24:43.793+0530 I CONTROL [initandlisten] ** WARNING: Access control is not enabled
for the database.
2018-03-01T16:24:43.793+0530 I CONTROL [initandlisten] ** Read and write access to data
and configuration is unrestricted.
2018-03-01T16:24:43.793+0530 I CONTROL [initandlisten]
MongoDB Enterprise > use mylearning
switched to db mylearning
MongoDB Enterprise > show collections
chats
colors
messages
MongoDB Enterprise > db.colors.count
function (query, options) {
query = this.find(query);
// Apply options and return the result of the find
return QueryHelpers._applyCountOptions(query, options).count(true);
}
MongoDB Enterprise > db.colors.count()
6
MongoDB Enterprise >
When you use count, make sure you are treating it as a function as count(). We have the count as 6, and that's what we are expecting. Am I right? Don't you think that we should go fetch some data from that collection, yeah with some filter?
MongoDB Enterprise > db.colors.find({"type": "primary"})
{ "_id" : ObjectId("5a97de7f2fcdf731d255a19d"), "color" : "black",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 255, 255, 255, 1 ], "hex" : "#000" } }
{ "_id" : ObjectId("5a97de7f2fcdf731d255a19e"), "color" : "yellow",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 255, 255, 0, 1 ], "hex" : "#FF0" } }
{ "_id" : ObjectId("5a97de7f2fcdf731d255a1a1"), "color" : "red",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 255, 0, 0, 1 ], "hex" : "#FF0" } }
{ "_id" : ObjectId("5a97de7f2fcdf731d255a1a2"), "color" : "blue",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 0, 0, 255, 1 ], "hex" : "#00F" } }
MongoDB Enterprise >
We have successfully imported that data, and we have fetched the colors with type as primary. I think there should be a custom color, which has the type as primary. Can we do that now?
MongoDB Enterprise > db.colors.insert({
... "color": "custome",
... "category": "hue",
... "type": "primary",
... "code": {
... "rgba": [255,1,255,1],
... "hex": "#FF1"
... }
... }
... )
WriteResult({ "nInserted" : 1 })
MongoDB Enterprise >
Now if you run our previous query, you can see an output as follows:
MongoDB Enterprise > db.colors.find({"type": "primary"})
{ "_id" : ObjectId("5a97de7f2fcdf731d255a19d"), "color" : "black",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 255, 255, 255, 1 ], "hex" : "#000" } }
{ "_id" : ObjectId("5a97de7f2fcdf731d255a19e"), "color" : "yellow",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 255, 255, 0, 1 ], "hex" : "#FF0" } }
{ "_id" : ObjectId("5a97de7f2fcdf731d255a1a1"), "color" : "red",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 255, 0, 0, 1 ], "hex" : "#FF0" } }
{ "_id" : ObjectId("5a97de7f2fcdf731d255a1a2"), "color" : "blue",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 0, 0, 255, 1 ], "hex" : "#00F" } }
{ "_id" : ObjectId("5a97e3202c19f0e958477e06"), "color" : "custome",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 255, 1, 255, 1 ], "hex" : "#FF1" } }
MongoDB Enterprise >
Updating a Document in MongoDB
Wow, we have the data now. And we performed Create and Read operations on our DB. It is time for updating the document. Let's go ahead and add a new property "manuallyCreated" to the color we have created. It is going to help us in finding these kind of entries easily.
MongoDB Enterprise > db.colors.update({
... "color":"custome"
... }
... ,{
... $set:{"manuallyCreated":"True"}}
... )
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
MongoDB Enterprise >
Let's find all the manually created colors now, and yeah we know there is going to be one record.
MongoDB Enterprise > db.colors.find({"manuallyCreated":"True"})
{ "_id" : ObjectId("5a97e3202c19f0e958477e06"), "color" : "custome",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 255, 1, 255, 1 ], "hex" : "#FF1" },
"manuallyCreated" : "True" }
MongoDB Enterprise >
Let's update the color name to "custom" instead of "custome", sorry for the typo.
MongoDB Enterprise > db.colors.update({"_id" : ObjectId("5a97e3202c19f0e958477e06")},
... {$set:{"color":"custom"}})
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
MongoDB Enterprise >
Ah, I made a mistake. I ran the following query by mistake:
MongoDB Enterprise > db.colors.update({ "color":"custom" } ,{ $set:{"code.rgba" : [ 255, 1, 255]}} )
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
Do you know what that query just did? It just updated the rgba of our custom color to three point array "[ 255, 1, 255]". That's not what I wanted. Now what can we do? We need to add one value to that set. Let's do that now.
MongoDB Enterprise > db.colors.update({ "color":"custom" } ,{ $addToSet:{"code.rgba" : "1" }} )
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
MongoDB Enterprise > db.colors.find({"manuallyCreated":"True"})
{ "_id" : ObjectId("5a97e3202c19f0e958477e06"), "color" : "custom",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 255, 1, 255, "1" ],
"hex" : "#FF1" }, "manuallyCreated" : "True" }
MongoDB Enterprise >
Please be noted that there is one more update, which will just update the entire document. In this case, if you are not providing the value for each attributes, it will be overwriting the same. Let's see an example.
MongoDB Enterprise > db.colors.update({"color":"red"},{"color":"test"})
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
MongoDB Enterprise > db.colors.find({})
Here, we just give a command to update the color red to color test, as we have not provided other attributes as part of our query, after running the query, there will be only one attribute, that is color.
MongoDB Enterprise > db.colors.find({})
{ "_id" : ObjectId("5a97f73f2fcdf731d255a1f1"), "color" : "black",
"category" : "hue", "type" : "primary", "code" : { "rgba" : [ 255, 255, 255, 1 ], "hex" : "#000" } }
{ "_id" : ObjectId("5a97f73f2fcdf731d255a1f2"), "color" : "test" }
{ "_id" : ObjectId("5a97f73f2fcdf731d255a1f3"),
"color" : "white", "category" : "value", "code" : { "rgba" : [ 0, 0, 0, 1 ], "hex" : "#FFF" } }
{ "_id" : ObjectId("5a97f73f2fcdf731d255a1f4"),
"color" : "blue", "category" : "hue", "type" : "primary", "code" :
{ "rgba" : [ 0, 0, 255, 1 ], "hex" : "#00F" } }
{ "_id" : ObjectId("5a97f73f2fcdf731d255a1f5"),
"color" : "yellow", "category" : "hue", "type" : "primary", "code" :
{ "rgba" : [ 255, 255, 0, 1 ], "hex" : "#FF0" } }
{ "_id" : ObjectId("5a97f73f2fcdf731d255a1f6"),
"color" : "green", "category" : "hue", "type" : "secondary", "code" :
{ "rgba" : [ 0, 255, 0, 1 ], "hex" : "#0F0" } }
MongoDB Enterprise > db.colors.find({"color":"test"})
{ "_id" : ObjectId("5a97f73f2fcdf731d255a1f2"), "color" : "test" }
MongoDB Enterprise >
Deleting a Document in MongoDB Shell
So, we added a custom color, and later we found that it is no more needed in our document as we found an exact match with a different color. Now we need to remove the one we have added.
MongoDB Enterprise > db.colors.remove({"color":"custom"})
WriteResult({ "nRemoved" : 1 })
MongoDB Enterprise >
Let's go and check again whether it is actually removed or not.
MongoDB Enterprise > db.colors.find({"color":"custom"})
MongoDB Enterprise >
The find query returns no records.
Deleting an Entire Collection
We have performed CRUD operations on a collection, what if we need to remove the entire collection?
MongoDB Enterprise > db.colors.drop()
true
MongoDB Enterprise >
With that, we are done with this post. I will be posting the continuation part of this series very soon. Till then, bye.
Conclusion
Thanks a lot for reading. Did I miss anything that you may think is needed? Could you find this post useful? I hope you liked this article. Please share your valuable suggestions and feedback.
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