R: Obtain a materialized table via a table store

tbl_get {pointblank}

R Documentation

Obtain a materialized table via a table store

Description

The tbl_get() function gives us the means to materialize a table that has an entry in a table store (i.e., has a table-prep formula with a unique name). The table store that is used for this can be in the form of a tbl_store object (created with the tbl_store() function) or an on-disk YAML representation of a table store (created by using yaml_write() with a tbl_store object).

Should you want a table-prep formula from a table store to use as a value for tbl (in create_agent(), create_informant(), or set_tbl()), then have a look at the tbl_source() function.

Usage

tbl_get(tbl, store = NULL)

Arguments

`tbl`	The table to retrieve from a table `store`. This table could be identified by its name (e.g., `tbl = "large_table"`) or by supplying a reference using a subset (with `$`) of the `tbl_store` object (e.g., `tbl = store$large_table`). If using the latter method then nothing needs to be supplied to `store`.
`store`	Either a table store object created by the `tbl_store()` function or a path to a table store YAML file created by `yaml_write()`.

Value

A table object.

Examples

Define a tbl_store object by adding several table-prep formulas in tbl_store().

store <- 
  tbl_store(
    small_table_duck ~ db_tbl(
      table = small_table,
      dbname = ":memory:",
      dbtype = "duckdb"
    ),
    ~ db_tbl(
      table = "rna",
      dbname = "pfmegrnargs",
      dbtype = "postgres",
      host = "hh-pgsql-public.ebi.ac.uk",
      port = 5432,
      user = I("reader"),
      password = I("NWDMCE5xdipIjRrp")
    ),
    sml_table ~ pointblank::small_table
  )

Once this object is available, we can access the tables named: "small_table_duck", "rna", and "sml_table". Let's check that the "rna" table is accessible through tbl_get():

tbl_get(
  tbl = "rna",
  store = store
)

## # Source:   table<rna> [?? x 9]
## # Database: postgres [reader@hh-pgsql-public.ebi.ac.uk:5432/pfmegrnargs]
##          id upi        timestamp           userstamp crc64   len seq_short
##     <int64> <chr>      <dttm>              <chr>     <chr> <int> <chr>    
##  1 24583872 URS000177… 2019-12-02 13:26:08 rnacen    C380…   511 ATTGAACG…
##  2 24583873 URS000177… 2019-12-02 13:26:08 rnacen    BC42…   390 ATGGGCGA…
##  3 24583874 URS000177… 2019-12-02 13:26:08 rnacen    19A5…   422 CTACGGGA…
##  4 24583875 URS000177… 2019-12-02 13:26:08 rnacen    66E1…   534 AGGGTTCG…
##  5 24583876 URS000177… 2019-12-02 13:26:08 rnacen    CC8F…   252 TACGTAGG…
##  6 24583877 URS000177… 2019-12-02 13:26:08 rnacen    19E4…   413 ATGGGCGA…
##  7 24583878 URS000177… 2019-12-02 13:26:08 rnacen    AE91…   253 TACGAAGG…
##  8 24583879 URS000177… 2019-12-02 13:26:08 rnacen    E21A…   304 CAGCAGTA…
##  9 24583880 URS000177… 2019-12-02 13:26:08 rnacen    1AA7…   460 CCTACGGG…
## 10 24583881 URS000177… 2019-12-02 13:26:08 rnacen    2046…   440 CCTACGGG…
## # … with more rows, and 2 more variables: seq_long <chr>, md5 <chr>

An alternative method for getting the same table materialized is by using $ to get the formula of choice from tbls and passing that to tbl_get(). The benefit of this is that we can use autocompletion to show us what's available in the table store (i.e., appears after typing the $).

store$small_table_duck %>% tbl_get()

## # Source:   table<small_table> [?? x 8]
## # Database: duckdb_connection
##    date_time           date           a b             c      d e     f    
##    <dttm>              <date>     <int> <chr>     <dbl>  <dbl> <lgl> <chr>
##  1 2016-01-04 11:00:00 2016-01-04     2 1-bcd-345     3  3423. TRUE  high 
##  2 2016-01-04 00:32:00 2016-01-04     3 5-egh-163     8 10000. TRUE  low  
##  3 2016-01-05 13:32:00 2016-01-05     6 8-kdg-938     3  2343. TRUE  high 
##  4 2016-01-06 17:23:00 2016-01-06     2 5-jdo-903    NA  3892. FALSE mid  
##  5 2016-01-09 12:36:00 2016-01-09     8 3-ldm-038     7   284. TRUE  low  
##  6 2016-01-11 06:15:00 2016-01-11     4 2-dhe-923     4  3291. TRUE  mid  
##  7 2016-01-15 18:46:00 2016-01-15     7 1-knw-093     3   843. TRUE  high 
##  8 2016-01-17 11:27:00 2016-01-17     4 5-boe-639     2  1036. FALSE low  
##  9 2016-01-20 04:30:00 2016-01-20     3 5-bce-642     9   838. FALSE high 
## 10 2016-01-20 04:30:00 2016-01-20     3 5-bce-642     9   838. FALSE high 
## # … with more rows

Function ID

1-10