2.2.3.5.5 Get Information about Datastore Contents
You can get information about a datastore in the current user schema by using the ore.datastore and ore.datastoreSummary functions.
Using the ore.datastore function, you can list basic information about datastores. To get information about a specific type of datastore, you can use the optional character string type argument. The valid values for typeare the following:
-
user, which lists the datastores created by current session user. This is the default value. -
private, which lists the datastores for which read access cannot be granted by the current session user to other users. -
all, which lists all of the datastores to which the current session user has read access. -
grantable, which lists the datastores the read privilege for which can be granted by the current session user to other users. -
grant, which lists the datastores the read privilege for which has been granted by the current session user to other users. -
granted, which lists the datastores the read privilege for which has been granted by other users to the current session user.
If you do not specify a type, then function ore.datastore returns a data.frame object with columns that correspond to the datastore name, the number of objects in the datastore, the datastore size, the creation date, and a description. Rows are sorted by column datastore.name in alphabetical order. If you do specify a type, then the function returns a data.framethat has a column for the specified type.
You can search for a datastore by name or by using a regular expression pattern.
The ore.datastoreSummary function returns information about the R objects saved within a datastore in the user schema in the connected database. The function returns a data.frame with columns that correspond to object name, object class, object size, and either the length of the object, if it is a vector, or the number of rows and columns, if it is a data.frame object. It takes one required argument, the name of a datastore, and has an optional argument, the owner of the datastore.
Example 2-20 Using the ore.datastore Function
This example demonstrates using the ore.datastore function.
# Create some R objects.df1 <- data.frame(x1 = 1:5, y1 = letters[1:5])
df2 <- data.frame(x2 = 5:1, y2 = letters[11:15])
iris_of <- ore.push(iris)
# Create a database table and an OML4R proxy object for the table.
ore.drop("AIRQUALITY")
ore.create(airquality, table = "AIRQUALITY")
# Save the objects to a datastore named ds1 and supply a description.
ore.save(AIRQUALITY, list = ls(), name = "ds1", description = "My private datastore")
# Create some more objects.
x <- stats::runif(20) # x is an object of type numeric.
y <- list(a = 1, b = TRUE, c = "hoopsa")
z <- ore.push(x) # z is an object of type ore.numeric.
# Create other datastores.
ore.save(x, y, name = "ds2", description = "x and y")
ore.save(df1, df2, name = "dfobj", description = "df objects")
ore.save(x, y, z, name = "another_ds", description = "For pattern matching")
# List all of the datastore objects.
ore.datastore()
# List the specified datastore.
ore.datastore("ds1")
# List the datastore objects with names that include "ds".
ore.datastore(pattern = "ds")
Listing for This Example
R> # Create some R objects.
R> df1 <- data.frame(x1 = 1:5, y1 = letters[1:5])
R> df2 <- data.frame(x2 = 5:1, y2 = letters[11:15])
R> iris_of <- ore.push(iris)
R>
R> # Create a database table and an OML4R proxy object for the table.
R> ore.drop("AIRQUALITY")
R> ore.create(airquality, table = "AIRQUALITY")
R>
R> # Save the objects to a datastore named ds1 and supply a description.
R> ore.save(AIRQUALITY, list = ls(), name = "ds1", description = "My private datastore")
R>
R> # Create some more objects.
R> x <- stats::runif(20) # x is an object of type numeric.
R> y <- list(a = 1, b = TRUE, c = "hoopsa")
R> z <- ore.push(x) # z is an object of type ore.numeric.
R>
R> # Create other datastores.
R> ore.save(x, y, name = "ds2", description = "x and y")
R> ore.save(df1, df2, name = "dfobj", description = "df objects")
R> ore.save(x, y, z, name = "another_ds", description = "For pattern matching")
R>
R> # List all of the datastore objects.
R> ore.datastore()
datastore.name object.count size creation.date description
1 another_ds 3 1284 2017-04-21 16:08:57 For pattern matching
2 dfobj 2 656 2017-04-21 16:08:38 df objects
3 ds1 4 3439 2017-04-21 16:03:55 My private datastore
4 ds2 2 314 2017-04-21 16:04:32 x and y
R> # List the specified datastore.
R> ore.datastore("ds1")
datastore.name object.count size creation.date description
1 ds1 4 3439 2017-04-21 16:03:55 My private datastore
R> # List the datastore objects with names that include "ds".
R> ore.datastore(pattern = "ds")
datastore.name object.count size creation.date description
1 another_ds 3 1284 2017-04-21 16:08:57 For pattern matching
2 ds1 4 3439 2017-04-21 16:03:55 My private datastore
3 ds2 2 314 2017-04-21 16:04:32 x and y
Example 2-21 Using the ore.datastoreSummary Function
This example demonstrates using the ore.datastoreSummary function. The example uses the datastores created in the previous example.
ore.datastoreSummary("ds1")
ore.datastoreSummary("ds2")Listing for This Example
R> ore.datastoreSummary("ds1")
object.name class size length row.count col.count
1 AIRQUALITY ore.frame 1213 6 NA 6
2 df1 data.frame 328 2 5 2
3 df2 data.frame 328 2 5 2
4 iris_of ore.frame 1570 5 NA 5
R> ore.datastoreSummary("ds2")
object.name class size length row.count col.count
1 x numeric 182 20 NA NA
2 y list 132 3 NA NAParent topic: Save and Manage R Objects in the Database