Retrieve data
Let’s check that the data was inserted.
Now let’s search for a particular record using a WHERE clause. The primary
key of the table can be used in the WHERE clause, but non-primary key columns
cannot be used unless indexed.
The following query, looking at the location
http://localhost:8080/graphql/library
will get both the title and the author for the specified book WHERE
title:"Moby Dick":
# get one book using the primary key title with a value
query oneBook {
book (value: {title:"Moby Dick"}) {
values {
title
author
}
}
}{
"data": {
"books": {
"values": [
{
"title": "Moby Dick",
"author": "Herman Melville"
}
]
}
}
}To find multiple books, an addition to the WHERE clause is required, to denote that
the list of titles desired is IN a group:
# get 3 books using the primary keys with an "in" filter clause of the primary key title
query ThreeBooks {
book(filter: { title: { in: ["Native Son", "Moby Dick", "Catch-22"] } } ) {
values {
title
author
}
}
}{
"data": {
"book": {
"values": [
{
"title": "Catch-22",
"author": "Joseph Heller"
},
{
"title": "Moby Dick",
"author": "Herman Melville"
}
]
}
}
}To display the contents of a UDT, notice the inclusion of addresses in the values displayed for this read query:
# query the author to see the UDT
query getReaderWithUDT{
reader(value: { name:"Allen Ginsberg" user_id: "e0ed81c3-0826-473e-be05-7de4b4592f64" }) {
values {
name
birthdate
addresses {
street
city
zip
}
}
}
}{
"data": {
"reader": {
"values": [
{
"name": "Allen Ginsberg",
"birthdate": "1926-06-03",
"addresses": [
{
"street": "Haight St",
"city": "San Francisco",
"zip": "94016"
}
]
}
]
}
}
}To display the contents of a map collection, notice the inclusion of earned in the values displayed for this read query:
# query a badge record that has a MAP (earned) with only the partition key
query oneGoldBadge {
badge(value: { badge_type: "Gold" } ) {
values {
badge_type
badge_id
earned {
key
value
}
}
}
}{
"data": {
"badge": {
"values": [
{
"badge_type": "Gold",
"badge_id": 100,
"earned": [
{
"key": "Writer",
"value": "2020-11-20"
}
]
}
]
}
}
}Filter options for reading
It’s possible to customize the condition of each parameter with WHERE
with the following arguments:
-
column: the GraphQL column name to which the condition applies
-
predicate: the conditional predicate to use
The filters available are:
Predicate |
columns that can have condition applied |
eq (equal) |
partition key, clustering column, regular indexed column |
notEq (not equal) |
partition key, clustering column, regular indexed column; allowed in conditional updates, but not selects |
in (within) |
partition key, clustering column, regular indexed column |
gt (greater than) |
clustering column |
gte (greater than or equal to) |
clustering column |
lt (less than) |
clustering column |
lte (less than or equal to) |
clustering column |
contains |
regular indexed column that is a , set or list, and has an index target of VALUES |
containsKey |
map contains the specified key |
containsEntry |
map contains the specified key:value pair |
Note that these can only be used with primary key columns, just like in Cassandra, unless indexing is created.
The next examples will query the same table, badge, using a variety of filters to illustrate
the versatility of such filters.
The first example finds the record that has the partition key badge_type equal to Gold, and
the badge_id equal to 100:
# query a badge record that has a MAP (earned) with the partition key and the clustering key
query oneGold100Badge {
badge(filter: { badge_type: {eq:"Gold"} badge_id: {eq:100}} ) {
values {
badge_type
badge_id
earned {
key
value
}
}
}
}{
"data": {
"badge": {
"values": [
{
"badge_type": "Gold",
"badge_id": 100,
"earned": [
{
"key": "Writer",
"value": "2020-11-20"
}
]
}
]
}
}
}Now if we use a different operator gt with the same query, notice that the query will fail,
because no badge_id greater than a value of 100 is found:
# query a badge record that has a MAP (earned) with the partition key and the clustering key
# filter badge_id: {gt:100 will fail}
query oneGold100BadgeFail {
badge(filter: { badge_type: {eq:"Gold"} badge_id: {gt:100}} ) {
values {
badge_type
badge_id
earned {
key
value
}
}
}
}{
"data": {
"badge": {
"values": []
}
}
}In order to use filters for any columns that are not part of the primary key, currently you need to use CQL to create a secondary index using the CQL shell. The next three examples show the CQL creation of an index in order to query a column that is a map collection.
In this example, an index is created on the keys of the map earned, so the containsKey
filter can be used to query in GraphQL.
# query a badge record that has a MAP (earned) with the partition key, clustering key, and a MAP key
# Requires: CREATE INDEX badge_idx ON library.badge(KEYS(earned));
query oneWriterBadge {
badge(filter: { badge_type: {eq:"Gold"} badge_id: {eq:100} earned: { containsKey: "Writer"} } ) {
values {
badge_type
badge_id
earned {
key
value
}
}
}
}{
"data": {
"badge": {
"values": [
{
"badge_type": "Gold",
"badge_id": 100,
"earned": [
{
"key": "Writer",
"value": "2020-11-20"
}
]
}
]
}
}
}Because the index now exists, it is also possible to just filter based on the map key itself:
# query a badge record that has a MAP (earned) with only a MAP key
# CREATE INDEX badge_idx ON library.badge(KEYS(earned));
query oneWriterKeyBadge {
badge(filter: { earned: { containsKey: "Writer"} } ) {
values {
badge_type
badge_id
earned {
key
value
}
}
}
}{
"data": {
"badge": {
"values": [
{
"badge_type": "Gold",
"badge_id": 100,
"earned": [
{
"key": "Writer",
"value": "2020-11-20"
}
]
}
]
}
}
}In this next example, an index is created on the values of the map earned, so the contains
filter can be used to query in GraphQL.
# query a badge record that has a MAP (earned) with only a MAP value
# Requires: CREATE INDEX badge2_idx ON library.badge(VALUES(earned));
query oneWriterValueBadge {
badge(filter: { earned: { contains: "2020-11-20"} } ) {
values {
badge_type
badge_id
earned {
key
value
}
}
}
}{
"data": {
"badge": {
"values": [
{
"badge_type": "Gold",
"badge_id": 100,
"earned": [
{
"key": "Writer",
"value": "2020-11-20"
}
]
}
]
}
}
}To make a complete set of filters, an index is created on the entries of the map earned, so the containsEntry
filter can be used to query in GraphQL.
# query a badge record that has a MAP (earned) with only a MAP entry
# Requires: CREATE INDEX badge3_idx ON library.badge(ENTRIES(earned));
query oneWriterEntryBadge {
badge(filter: { earned: { containsEntry: {key:"Writer", value:"2020-11-20"}} } ) {
values {
badge_type
badge_id
earned {
key
value
}
}
}
}{
"data": {
"badge": {
"values": [
{
"badge_type": "Gold",
"badge_id": 100,
"earned": [
{
"key": "Writer",
"value": "2020-11-20"
}
]
}
]
}
}
}