Database Manual / Reference / Query Language / Query Predicates / Bitwise

$bitsAnyClear

$bitsAnyClear

$bitsAnyClear matches documents where any of the bit positions given by the query are clear (i.e. 0) in field.匹配字段中查询给出的任何位位置都是明确的（即0）的文档。

{ <field>: { $bitsAnyClear: <numeric bitmask> } }
{ <field>: { $bitsAnyClear: < BinData bitmask> } }
{ <field>: { $bitsAnyClear: [ <position1>, <position2>, ... ] } }

The field value must be either numeric or a BinData instance. Otherwise, $bitsAnyClear will not match the current document.field值必须是数字或BinData实例。否则，$bitsAnyClear将与当前文档不匹配。

Numeric Bitmask数字位掩码
You can provide a numeric bitmask to be matched against the operand field. The bitmask must be a non-negative 64-bit signed integer. Otherwise, $bitsAnyClear returns an error.您可以提供与操作数字段匹配的数字位掩码。位掩码必须是非负的64位带符号整数。否则，$bitsAnyClear将返回错误。
BinData Bitmask位掩码
You can also use an arbitrarily large BinData instance as a bitmask.您还可以使用任意大的BinData实例作为位掩码。
Position List职位列表
If querying a list of bit positions, each <position> must be a non-negative integer. Bit positions start at 0 from the least significant bit. For example, the decimal number 254 would have the following bit positions:如果查询位位置列表，则每个<position>必须是非负整数。位位置从最低有效位的0开始。例如，十进制数254将具有以下位位置：
Bit Value位值11111110
Position位置76543210

Behavior行为

The endianness of your system depends on the architecture of your machine. 系统的端序取决于机器的架构。Numbers in BSON data are always stored as little-endian, if your system is big-endian this means that numeric data is converted between big and little endian.BSON数据中的数字始终以小端存储，如果系统是大端，这意味着数字数据在大端和小端之间转换。

In the context of the bit-test match expression operators:在比特测试匹配表达式运算符的上下文中：

BinData values act as bitmasks and are interpreted as though they are arbitrary-length unsigned little-endian numbers. 值充当位掩码，并被解释为任意长度的无符号小端数字。The lowest-addressable byte is always interpreted as the least significant byte. Similarly, the highest-addressable byte in the BinData is always interpreted as the most significant byte.最低可寻址字节始终被解释为最低有效字节。同样，BinData中最高可寻址字节始终被解释为最高有效字节。

Indexes索引

Queries cannot use indexes for the $bitsAnyClear portion of a query, although the other portions of a query can use indexes, if applicable.查询不能对查询的$bitsAnyClear部分使用索引，但查询的其他部分可以使用索引（如果适用）。

Floating Point Values浮点值

$bitsAnyClear will not match numerical values that cannot be represented as a signed 64-bit integer. This can be the case if a value is either too large or too small to fit in a signed 64-bit integer, or if it has a fractional component.将不匹配不能表示为带符号64位整数的数值。如果一个值太大或太小，无法容纳一个有符号的64位整数，或者它有一个分数分量，则可能会出现这种情况。

Sign Extension符号扩展

Numbers are sign extended. For example, $bitsAnyClear considers bit position 200 to be set for the negative number -5, but bit position 200 to be clear for the positive number +5.数字是符号扩展的。例如，$bitsAnyClear认为位位置200设置为负数-5，但位位置200为正数+5。

In contrast, BinData instances are zero-extended. For example, given the following document:相比之下，BinData实例是零扩展的。例如，给定以下文档：

db.collection.insertOne({ x: BinData(0, "ww=="), binaryValueofA: "11000011" })

$bitsAnyClear will consider all bits outside of x to be clear.将认为x之外的所有位都是清晰的。

Examples示例

The following examples will use a collection with the following documents:以下示例将使用包含以下文档的集合：

db.collection.insertMany([
  { _id: 1, a: 54, binaryValueofA: "00110110" },
  { _id: 2, a: 20, binaryValueofA: "00010100" },
  { _id: 3, a: 20.0, binaryValueofA: "00010100" },
  { _id: 4, a: BinData(0, "Zg=="), binaryValueofA: "01100110" }
])

Bit Position Array位位置数组

The following query uses the $bitsAnyClear operator to test whether field a has either bit position 1 or bit position 5 clear, where the least significant bit is position 0.以下查询使用$bitsAnyClear运算符来测试字段a的位位置是1还是5，其中最低有效位是位置0。

db.collection.find( { a: { $bitsAnyClear: [ 1, 5 ] } } )

The query matches the following documents:查询匹配以下文档：

{ "_id" : 2, "a" : 20, "binaryValueofA" : "00010100" }
{ "_id" : 3, "a" : 20.0, "binaryValueofA" : "00010100" }

Integer Bitmask整数位掩码

The following query uses the $bitsAnyClear operator to test whether field a has any bits clear at positions 0, 1, and 5 (the binary representation of the bitmask 35 is 00100011).以下查询使用$bitsAnyClear运算符来测试字段a在位置0、1和5是否有任何位清除（位掩码35的二进制表示为00100011）。

db.collection.find( { a: { $bitsAnyClear: 35 } } )

The query matches the following documents:查询匹配以下文档：

{ "_id" : 1, "a" : 54, "binaryValueofA" : "00110110" }
{ "_id" : 2, "a" : 20, "binaryValueofA" : "00010100" }
{ "_id" : 3, "a" : 20.0, "binaryValueofA" : "00010100" }
{ "_id" : 4, "a" : BinData(0,"Zg=="), "binaryValueofA" : "01100110" }

BinData Bitmask位掩码

The following query uses the $bitsAnyClear operator to test whether field a has any bits clear at positions 4 and 5 (the binary representation of BinData(0, "MA==") is 00110000).以下查询使用$bitsAnyClear运算符来测试字段a在位置4和5是否有任何位是空的（BinData(0, "MA==")的二进制表示为00110000）。

db.collection.find( { a: { $bitsAnyClear: BinData(0, "MA==") } } )

The query matches the following documents:查询匹配以下文档：

{ "_id" : 2, "a" : 20, "binaryValueofA" : "00010100" }
{ "_id" : 3, "a" : 20.0, "binaryValueofA" : "00010100" }
{ "_id" : 4, "a" : BinData(0,"Zg=="), "binaryValueofA" : "01100110" }