Query Class — `Query`¶

`Query`¶

The query object created by calling aerospike.Client.query() is used for executing queries over a secondary index of a specified set (which can be omitted or None). For queries, the None set contains those records which are not part of any named set.

The query can (optionally) be assigned one of the following

One of the predicates (between() or equals()) using where().

A list of predexp using predexp()

A query without a predicate will match all the records in the given set, similar to a Scan.

The query is invoked using foreach(), results(), or execute_background() The bins returned can be filtered by using select().

If a list of write operations is added to the query with add_ops(), they will be applied to each record processed by the query. See available write operations at See aerospike_helpers

Finally, a stream UDF may be applied with apply(). It will aggregate results out of the records streaming back from the query.

See also

Queries and Managing Queries.

Query Methods¶

class aerospike.Query¶

select(bin1[, bin2[, bin3..]])¶: Set a filter on the record bins resulting from results() or foreach(). If a selected bin does not exist in a record it will not appear in the bins portion of that record tuple.

where(predicate)¶

Set a where predicate for the query, without which the query will behave similar to aerospike.Scan. The predicate is produced by one of the aerospike.predicates methods equals() and between().

Parameters:	predicate (tuple) – the `tuple()` produced by one of the `aerospike.predicates` methods.

Note

Currently, you can assign at most one predicate to the query.

results([,policy [, options]]) -> list of (key, meta, bins)¶

Buffer the records resulting from the query, and return them as a list of records.

Parameters:	policy (dict) – optional Query Policies. options (dict) – optional Query Options.
Returns:	a `list` of Record Tuple.

import aerospike
from aerospike import predicates as p
import pprint

config = { 'hosts': [ ('127.0.0.1', 3000)]}
client = aerospike.client(config).connect()

pp = pprint.PrettyPrinter(indent=2)
query = client.query('test', 'demo')
query.select('name', 'age') # matched records return with the values of these bins
# assuming there is a secondary index on the 'age' bin of test.demo
query.where(p.equals('age', 40))
records = query.results( {'total_timeout':2000})
pp.pprint(records)
client.close()

Note

Queries require a secondary index to exist on the bin being queried.

Note

Python client version >= 3.10.0 Supports predicate expressions for results, foreach, and execute_background see predexp. Requires server versions >= 4.7.0.

from __future__ import print_function
import aerospike
from aerospike import predexp
from aerospike import exception as ex
import sys
import time

config = {"hosts": [("127.0.0.1", 3000)]}
client = aerospike.client(config).connect()

# register udf
try:
    client.udf_put(
        "/path/to/my_udf.lua"
    )
except ex.AerospikeError as e:
    print("Error: {0} [{1}]".format(e.msg, e.code))
    client.close()
    sys.exit(1)

# put records and apply udf
try:
    keys = [("test", "demo", 1), ("test", "demo", 2), ("test", "demo", 3)]
    records = [{"number": 1}, {"number": 2}, {"number": 3}]
    for i in range(3):
        client.put(keys[i], records[i])

    try:
        client.index_integer_create("test", "demo", "number", "test_demo_number_idx")
    except ex.IndexFoundError:
        pass

    query = client.query("test", "demo")
    query.apply("my_udf", "my_udf", ["number", 10])
    job_id = query.execute_background()

    # wait for job to finish
    while True:
        response = client.job_info(job_id, aerospike.JOB_SCAN)
        print(response)
        if response["status"] != aerospike.JOB_STATUS_INPROGRESS:
            break
        time.sleep(0.25)

    records = client.get_many(keys)
    print(records)
except ex.AerospikeError as e:
    print("Error: {0} [{1}]".format(e.msg, e.code))
    sys.exit(1)
finally:
    client.close()
# EXPECTED OUTPUT:
# [
#   (('test', 'demo', 1, bytearray(b'\xb7\xf4\xb88\x89\xe2\xdag\xdeh>\x1d\xf6\x91\x9a\x1e\xac\xc4F\xc8')), {'gen': 2, 'ttl': 2591999}, {'number': 11}),
#   (('test', 'demo', 2, bytearray(b'\xaejQ_7\xdeJ\xda\xccD\x96\xe2\xda\x1f\xea\x84\x8c:\x92p')), {'gen': 12, 'ttl': 2591999}, {'number': 12}),
#   (('test', 'demo', 3, bytearray(b'\xb1\xa5`g\xf6\xd4\xa8\xa4D9\xd3\xafb\xbf\xf8ha\x01\x94\xcd')), {'gen': 13, 'ttl': 2591999}, {'number': 13})
# ]

# contents of my_udf.lua
function my_udf(rec, bin, offset)
    info("my transform: %s", tostring(record.digest(rec)))
    rec[bin] = rec[bin] + offset
    aerospike:update(rec)
end

Note

For a similar example using .results() see aerospike.Scan.results().

foreach(callback[, policy[, options]])¶

Invoke the callback function for each of the records streaming back from the query.

Parameters:	callback (callable) – the function to invoke for each record. policy (dict) – optional Query Policies. options (dict) – optional Query Options.

Note

A Record Tuple is passed as the argument to the callback function.

import aerospike
from aerospike import predicates as p
import pprint

config = { 'hosts': [ ('127.0.0.1', 3000)]}
client = aerospike.client(config).connect()

pp = pprint.PrettyPrinter(indent=2)
query = client.query('test', 'demo')
query.select('name', 'age') # matched records return with the values of these bins
# assuming there is a secondary index on the 'age' bin of test.demo
query.where(p.between('age', 20, 30))
names = []
def matched_names(record):
    key, metadata, bins = record
    pp.pprint(bins)
    names.append(bins['name'])

query.foreach(matched_names, {'total_timeout':2000})
pp.pprint(names)
client.close()

Note

To stop the stream return False from the callback function.

from __future__ import print_function
import aerospike
from aerospike import predicates as p

config = { 'hosts': [ ('127.0.0.1',3000)]}
client = aerospike.client(config).connect()

def limit(lim, result):
    c = [0] # integers are immutable so a list (mutable) is used for the counter
    def key_add(record):
        key, metadata, bins = record
        if c[0] < lim:
            result.append(key)
            c[0] = c[0] + 1
        else:
            return False
    return key_add

query = client.query('test','user')
query.where(p.between('age', 20, 30))
keys = []
query.foreach(limit(100, keys))
print(len(keys)) # this will be 100 if the number of matching records > 100
client.close()

apply(module, function[, arguments])¶

Aggregate the results() using a stream UDF. If no predicate is attached to the Query the stream UDF will aggregate over all the records in the specified set.

Parameters:	module (str) – the name of the Lua module. function (str) – the name of the Lua function within the module. arguments (list) – optional arguments to pass to the function. NOTE: these arguments must be types supported by Aerospike See: supported data types. If you need to use an unsuported type, (e.g. set or tuple) you can use a serializer like pickle first.
Returns:	one of the supported types, `int`, `str`, `float` (double), `list`, `dict` (map), `bytearray` (bytes).

See also

Developing Stream UDFs

Note

Assume we registered the following Lua module with the cluster as stream_udf.lua using aerospike.Client.udf_put().

local function having_ge_threshold(bin_having, ge_threshold)
    return function(rec)
        debug("group_count::thresh_filter: %s >  %s ?", tostring(rec[bin_having]), tostring(ge_threshold))
        if rec[bin_having] < ge_threshold then
            return false
        end
        return true
    end
end

local function count(group_by_bin)
  return function(group, rec)
    if rec[group_by_bin] then
      local bin_name = rec[group_by_bin]
      group[bin_name] = (group[bin_name] or 0) + 1
      debug("group_count::count: bin %s has value %s which has the count of %s", tostring(bin_name), tostring(group[bin_name]))
    end
    return group
  end
end

local function add_values(val1, val2)
  return val1 + val2
end

local function reduce_groups(a, b)
  return map.merge(a, b, add_values)
end

function group_count(stream, group_by_bin, bin_having, ge_threshold)
  if bin_having and ge_threshold then
    local myfilter = having_ge_threshold(bin_having, ge_threshold)
    return stream : filter(myfilter) : aggregate(map{}, count(group_by_bin)) : reduce(reduce_groups)
  else
    return stream : aggregate(map{}, count(group_by_bin)) : reduce(reduce_groups)
  end
end

Find the first name distribution of users in their twenties using a query aggregation:

import aerospike
from aerospike import predicates as p
import pprint

config = {'hosts': [('127.0.0.1', 3000)],
          'lua': {'system_path':'/usr/local/aerospike/lua/',
                  'user_path':'/usr/local/aerospike/usr-lua/'}}
client = aerospike.client(config).connect()

pp = pprint.PrettyPrinter(indent=2)
query = client.query('test', 'users')
query.where(p.between('age', 20, 29))
query.apply('stream_udf', 'group_count', [ 'first_name' ])
names = query.results()
# we expect a dict (map) whose keys are names, each with a count value
pp.pprint(names)
client.close()

With stream UDFs, the final reduce steps (which ties the results from the reducers of the cluster nodes) executes on the client-side. Explicitly setting the Lua user_path in the config helps the client find the local copy of the module containing the stream UDF. The system_path is constructed when the Python package is installed, and contains system modules such as aerospike.lua, as.lua, and stream_ops.lua. The default value for the Lua system_path is /usr/local/aerospike/lua.

add_ops(ops)¶

Add a list of write ops to the query. When used with Query.execute_background() the query will perform the write ops on any records found. If no predicate is attached to the Query it will apply ops to all the records in the specified set.

Parameters:	ops – list A list of write operations generated by the aerospike_helpers e.g. list_operations, map_operations, etc.

Note

Requires server version >= 4.7.0.

import aerospike
from aerospike_helpers.operations import list_operations
from aerospike_helpers.operations import operations
query = client.query('test', 'demo')

ops =  [
    operations.append(test_bin, 'val_to_append'),
    list_operations.list_remove_by_index(test_bin, list_index_to_remove, aerospike.LIST_RETURN_NONE)
]
query.add_ops(ops)

id = query.execute_background()
client.close()

For a more comprehensive example, see using a list of write ops with Query.execute_background() .

predexp(predicates)¶

Set the predicate expression filters to be used by this query.

Parameters:	predicates – list A list of predicates generated by the aerospike.predexp — Query Predicate Expressions functions

import aerospike
from aerospike import predexp as predexp
query = client.query('test', 'demo')

predexps =  [
    predexp.rec_device_size(),
    predexp.integer_value(65 * 1024),
    predexp.integer_greater()
]
query.predexp(predexps)

big_records = query.results()
client.close()

execute_background([policy])¶

Execute a record UDF or write operations on records found by the query in the background. This method returns before the query has completed. A UDF or a list of write operations must have been added to the query with Query.apply() or Query.add_ops() respectively.

Parameters:	policy (dict) – optional Write Policies.
Returns:	a job ID that can be used with `aerospike.Client.job_info()` to track the status of the `aerospike.JOB_QUERY` , as it runs in the background.

# Using a record UDF
import aerospike
query = client.query('test', 'demo')
query.apply('myudfs', 'myfunction', ['a', 1])
query_id = query.execute_background()
# This id can be used to monitor the progress of the background query

# Using a list of write ops.
from __future__ import print_function
import aerospike
from aerospike import predicates
from aerospike import exception as ex
from aerospike_helpers.operations import list_operations
import sys
import time

# Configure the client.
config = {"hosts": [("127.0.0.1", 3000)]}

# Create a client and connect it to the cluster.
try:
    client = aerospike.client(config).connect()
except ex.ClientError as e:
    print("Error: {0} [{1}]".format(e.msg, e.code))
    sys.exit(1)

TEST_NS = "test"
TEST_SET = "demo"
nested_list = [{"name": "John", "id": 100}, {"name": "Bill", "id": 200}]
# Write the records.
try:
    keys = [(TEST_NS, TEST_SET, i) for i in range(5)]
    for i, key in enumerate(keys):
        client.put(key, {"account_number": i, "members": nested_list})
except ex.RecordError as e:
    print("Error: {0} [{1}]".format(e.msg, e.code))

# EXAMPLE 1: Append a new account member to all accounts.
try:
    new_member = {"name": "Cindy", "id": 300}

    ops = [list_operations.list_append("members", new_member)]

    query = client.query(TEST_NS, TEST_SET)
    query.add_ops(ops)
    id = query.execute_background()
    # allow for query to complete
    time.sleep(3)
    print("EXAMPLE 1")

    for i, key in enumerate(keys):
        _, _, bins = client.get(key)
        print(bins)
except ex.ClientError as e:
    print("Error: {0} [{1}]".format(e.msg, e.code))
    sys.exit(1)

# EXAMPLE 2: Remove a member from a specific account using predicates.
try:
    # Add index to the records for use with predex.
    client.index_integer_create(
        TEST_NS, TEST_SET, "account_number", "test_demo_account_number_idx"
    )

    ops = [
        list_operations.list_remove_by_index("members", 0, aerospike.LIST_RETURN_NONE)
    ]

    query = client.query(TEST_NS, TEST_SET)
    number_predicate = predicates.equals("account_number", 3)
    query.where(number_predicate)
    query.add_ops(ops)
    id = query.execute_background()
    # allow for query to complete
    time.sleep(3)
    print("EXAMPLE 2")

    for i, key in enumerate(keys):
        _, _, bins = client.get(key)
        print(bins)
except ex.ClientError as e:
    print("Error: {0} [{1}]".format(e.msg, e.code))
    sys.exit(1)

# Cleanup and close the connection to the Aerospike cluster.
for i, key in enumerate(keys):
    client.remove(key)
client.index_remove(TEST_NS, "test_demo_account_number_idx")
client.close()

"""
EXPECTED OUTPUT:
EXAMPLE 1
{'account_number': 0, 'members': [{'name': 'John', 'id': 100}, {'name': 'Bill', 'id': 200}, {'name': 'Cindy', 'id': 300}]}
{'account_number': 1, 'members': [{'name': 'John', 'id': 100}, {'name': 'Bill', 'id': 200}, {'name': 'Cindy', 'id': 300}]}
{'account_number': 2, 'members': [{'name': 'John', 'id': 100}, {'name': 'Bill', 'id': 200}, {'name': 'Cindy', 'id': 300}]}
{'account_number': 3, 'members': [{'name': 'John', 'id': 100}, {'name': 'Bill', 'id': 200}, {'name': 'Cindy', 'id': 300}]}
{'account_number': 4, 'members': [{'name': 'John', 'id': 100}, {'name': 'Bill', 'id': 200}, {'name': 'Cindy', 'id': 300}]}
EXAMPLE 2
{'account_number': 0, 'members': [{'name': 'John', 'id': 100}, {'name': 'Bill', 'id': 200}, {'name': 'Cindy', 'id': 300}]}
{'account_number': 1, 'members': [{'name': 'John', 'id': 100}, {'name': 'Bill', 'id': 200}, {'name': 'Cindy', 'id': 300}]}
{'account_number': 2, 'members': [{'name': 'John', 'id': 100}, {'name': 'Bill', 'id': 200}, {'name': 'Cindy', 'id': 300}]}
{'account_number': 3, 'members': [{'name': 'Bill', 'id': 200}, {'name': 'Cindy', 'id': 300}]}
{'account_number': 4, 'members': [{'name': 'John', 'id': 100}, {'name': 'Bill', 'id': 200}, {'name': 'Cindy', 'id': 300}]}
"""

Query Policies¶

policy

A dict of optional query policies which are applicable to Query.results() and Query.foreach(). See Policy Options.

max_retries int

Maximum number of retries before aborting the current transaction. The initial attempt is not counted as a retry.

If max_retries is exceeded, the transaction will return error AEROSPIKE_ERR_TIMEOUT.

Default: 0

Warning

: Database writes that are not idempotent (such as “add”) should not be retried because the write operation may be performed multiple times if the client timed out previous transaction attempts. It’s important to use a distinct write policy for non-idempotent writes which sets max_retries = 0;
sleep_between_retries int

Milliseconds to sleep between retries. Enter 0 to skip sleep.

Default: 0
socket_timeout int

Socket idle timeout in milliseconds when processing a database command.

If socket_timeout is not 0 and the socket has been idle for at least socket_timeout, both max_retries and total_timeout are checked. If max_retries and total_timeout are not exceeded, the transaction is retried.

If both socket_timeout and total_timeout are non-zero and socket_timeout > total_timeout, then socket_timeout will be set to total_timeout. If socket_timeout is 0, there will be no socket idle limit.

Default: 30000.
total_timeout int

Total transaction timeout in milliseconds.

The total_timeout is tracked on the client and sent to the server along with the transaction in the wire protocol. The client will most likely timeout first, but the server also has the capability to timeout the transaction.

If total_timeout is not 0 total_timeout is reached before the transaction completes, the transaction will return error AEROSPIKE_ERR_TIMEOUT. If total_timeout is 0, there will be no total time limit.

Default: 0
deserialize bool

Should raw bytes representing a list or map be deserialized to a list or dictionary.

Set to False for backup programs that just need access to raw bytes.

Default: True
fail_on_cluster_change bool

Terminate query if cluster is in migration state.

Default False

Query Options¶

options

A dict of optional scan options which are applicable to Query.foreach() and Query.results().

nobins bool

Whether to return the bins portion of the Record Tuple.

Default False.

New in version 3.0.0.

Query Class — Query¶

Query¶

Query Methods¶

Query Policies¶

Query Options¶

Query Class — `Query`¶

`Query`¶