AsterixDB supports the CSV format for both data input and query result output. In both cases, the structure of the CSV data must be defined using a named ADM record datatype. The CSV format, limitations, and MIME type are defined by RFC 4180.
CSV is not as expressive as the full Asterix Data Model, meaning that not all data which can be represented in ADM can also be represented as CSV. So the form of this datatype is limited. First, obviously it may not contain any nested records or lists, as CSV has no way to represent nested data structures. All fields in the record type must be primitive. Second, the set of supported primitive types is limited to numerics (int8, int16, int32, int64, float, double) and string. On output, a few additional primitive types (boolean, datetime types) are supported and will be represented as strings.
For the purposes of this document, we will use the following dataverse and datatype definitions:
drop dataverse csv if exists;
create dataverse csv;
use dataverse csv;
create type "csv_type" as closed {
"id": int32,
"money": float,
"name": string
};
create dataset "csv_set" ("csv_type") primary key "id";
Note: There is no explicit restriction against using an open datatype for CSV purposes, and you may have optional fields in the datatype (eg., id: int32?). However, the CSV format itself is rigid, so using either of these datatype features introduces possible failure modes on output which will be discussed below.
CSV data may be loaded into a dataset using the normal "load dataset" mechanisms, utilizing the builtin "delimited-text" format. See Accessing External Data for more details. Note that comma is the default value for the "delimiter" parameter, so it does not need to be explicitly specified.
In this case, the datatype used to interpret the CSV data is the datatype associated with the dataset being loaded. So, to load a file that we have stored locally on the NC into our example dataset:
use dataverse csv;
load dataset "csv_set" using localfs
(("path"="127.0.0.1:///tmp/my_sample.csv"),
("format"="delimited-text"));
So, if the file /tmp/my_sample.csv contained
1,18.50,"Peter Krabnitz" 2,74.50,"Jesse Stevens"
then the preceding query would load it into the dataset csv_set.
If your CSV file has a header (that is, the first line contains a set of field names, rather than actual data), you can instruct Asterix to ignore this header by adding the parameter "header"="true", eg.
load dataset "csv_set" using localfs
(("path"="127.0.0.1:///tmp/my_header_sample.csv"),
("format"="delimited-text"),
("header"="true"));
This is useful when the CSV file was produced from an earlier AsterixDB operation, as AsterixDB's CSV output always has a header line.
CSV data may also be loaded from HDFS; see Accessing External Data for details. However please note that CSV files on HDFS cannot have headers; attempting to specify "header"="true" when reading from HDFS could result in non-header lines of data being skipped as well.
Any query may be rendered as CSV when using AsterixDB's HTTP interface. To do so, there are two steps required: specify the record type which defines the schema of your CSV, and request that Asterix use the CSV output format.
Background: The result of any AQL query is an unordered list of instances, where each instance is an instance of an AQL datatype. When requesting CSV output, there are some restrictions on the legal datatypes in this unordered list due to the limited expressability of CSV:
While it would be possible to structure your query to cast all result instances to a given type, it is not necessary. AQL offers a built-in feature which will automatically cast all top-level instances in the result to a specified named ADM record type. To enable this feature, use a set statement prior to the query to set the parameter output-record-type to the name of an ADM type. This type must have already been defined in the current dataverse.
For example, the following request will ensure that all result instances are cast to the csv_type type declared earlier:
use dataverse csv; set output-record-type "csv_type"; for $n in dataset "csv_set" return $n;
In this case the casting is redundant since by definition every value in csv_set is already of type csv_type. But consider a more complex query where the result values are created by joining fields from different underlying datasets, etc.
Two notes about output-record-type:
output-record-type is in fact required, not optional. This is because the type is used to determine the field names for the CSV header and to ensure that the ordering of fields in the output is consistent (which is obviously vital for the CSV to make any sense).When sending requests to the Asterix HTTP API, Asterix decides what format to use for rendering the results based on the Accept HTTP header. By default, Asterix will produce JSON output, and this can be requested explicitly by specifying the MIME type application/json. To select CSV output, set the Accept header on your request to the MIME type text/csv. The details of how to accomplish this will of course depend on what tools you are using to contact the HTTP API. Here is an example from a Unix shell prompt using the command-line utility "curl":
curl -G -H "Accept: text/csv" "http://localhost:19002/query" --data-urlencode '
query=use dataverse csv;
set output-record-type "csv_type";
for $n in dataset csv_set return $n;'
Similarly, a trivial Java program to execute the above sample query would be:
import java.net.HttpURLConnection;
import java.net.URL;
import java.net.URLEncoder;
import java.io.BufferedReader;
import java.io.InputStream;
import java.io.InputStreamReader;
public class AsterixExample {
public static void main(String[] args) throws Exception {
String query = "use dataverse csv; " +
"set output-record-type \"csv_type\";" +
"for $n in dataset csv_set return $n";
URL asterix = new URL("http://localhost:19002/query?query=" +
URLEncoder.encode(query, "UTF-8"));
HttpURLConnection conn = (HttpURLConnection) asterix.openConnection();
conn.setRequestProperty("Accept", "text/csv");
BufferedReader result = new BufferedReader
(new InputStreamReader(conn.getInputStream()));
String line;
while ((line = result.readLine()) != null) {
System.out.println(line);
}
result.close();
}
}
For either of the above examples, the output would be:
"id","money","name" 1,18.5,"Peter Krabnitz" 2,74.5,"Jesse Stevens"
assuming you had already run the previous examples to create the dataverse and populate the dataset.
As mentioned earlier, CSV is a rigid format. It cannot express records with different numbers of fields, which ADM allows through both open datatypes and optional fields.
If your output record type contains optional fields, this will not result in any errors. If the output data of a query does not contain values for an optional field, this will be represented in CSV as null.
If your output record type is open, this will also not result in any errors. If the output data of a query contains any open fields, the corresponding rows in the resulting CSV will contain more comma-separated values than the others. On each such row, the data from the closed fields in the type will be output first in the normal order, followed by the data from the open fields in an arbitrary order.
According to RFC 4180 this is not strictly valid CSV (Section 2, rule 4, "Each line should contain the same number of fields throughout the file"). Hence it will likely not be handled consistently by all CSV processors. Some may throw a parsing error. If you attempt to load this data into AsterixDB later using load dataset, the extra fields will be silently ignored. For this reason it is recommended that you use only closed datatypes as output record types. AsterixDB allows to use an open record type only to support cases where the type already exists for other parts of your application.