2015-01-10 20:44:26 +01:00
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package schema
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import (
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"fmt"
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"reflect"
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"strconv"
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"strings"
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"sync"
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"github.com/mitchellh/mapstructure"
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)
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// MapFieldWriter writes data into a single map[string]string structure.
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type MapFieldWriter struct {
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Schema map[string]*Schema
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lock sync.Mutex
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result map[string]string
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}
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// Map returns the underlying map that is being written to.
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func (w *MapFieldWriter) Map() map[string]string {
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w.lock.Lock()
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defer w.lock.Unlock()
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if w.result == nil {
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w.result = make(map[string]string)
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}
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return w.result
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}
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core: Allow dynamic attributes in helper/schema
The helper/schema framework for building providers previously validated
in all cases that each field being set in state was in the schema.
However, in order to support remote state in a usable fashion, the need
has arisen for the top level attributes of the resource to be created
dynamically. In order to still be able to use helper/schema, this commit
adds the capability to assign additional fields.
Though I do not forsee this being used by providers other than remote
state (and that eventually may move into Terraform Core rather than
being a provider), the usage and semantics are:
To opt into dynamic attributes, add a schema attribute named
"__has_dynamic_attributes", and make it an optional string with no
default value, in order that it does not appear in diffs:
"__has_dynamic_attributes": {
Type: schema.TypeString
Optional: true
}
In the read callback, use the d.UnsafeSetFieldRaw(key, value) function
to set the dynamic attributes.
Note that other fields in the schema _are_ copied into state, and that
the names of the schema fields cannot currently be used as dynamic
attribute names, as we check to ensure a value is not already set for a
given key.
2016-06-11 12:23:32 +02:00
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func (w *MapFieldWriter) unsafeWriteField(addr string, value string) {
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w.lock.Lock()
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defer w.lock.Unlock()
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if w.result == nil {
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w.result = make(map[string]string)
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}
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w.result[addr] = value
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}
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helper/schema: Clear existing map/set/list contents before overwriting
There are situations where one may need to write to a set, list, or map
more than once per single TF operation (apply/refresh/etc). In these
cases, further writes using Set (example: d.Set("some_set", newSet))
currently create unstable results in the set writer (the name of the
writer layer that holds the data set by these calls) because old keys
are not being cleared out first.
This bug is most visible when using sets. Example: First write to set
writes elements that have been hashed at 10 and 20, and the second write
writes elements that have been hashed at 30 and 40. While the set length
has been correctly set at 2, since a set is basically a map (as is the
entire map writer) and map results are non-deterministic, reads to this
set will now deliver unstable results in a random but predictable
fashion as the map results are delivered to the caller non-deterministic
- sometimes you may correctly get 30 and 40, but sometimes you may get
10 and 20, or even 10 and 30, etc.
This problem propagates to state which is even more damaging as unstable
results are set to state where they become part of the permanent data
set going forward.
The problem also applies to lists and maps. This is probably more of an
issue with maps as a map can contain any key/value combination and hence
there is no predictable pattern where keys would be overwritten with
default or zero values. This is contrary to complex lists, which has
this problem as well, but since lists are deterministic and the length
of a list properly gets updated during the overwrite, the problem is
masked by the fact that a read will only read to the boundary of the
list, skipping any bad data that may still be available due past the
list boundary.
This update clears the child contents of any set, list, or map before
beginning a new write to address this issue. Tests are included for all
three data types.
2017-11-05 20:14:51 +01:00
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// clearTree clears a field and any sub-fields of the given address out of the
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// map. This should be used to reset some kind of complex structures (namely
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// sets) before writing to make sure that any conflicting data is removed (for
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// example, if the set was previously written to the writer's layer).
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func (w *MapFieldWriter) clearTree(addr []string) {
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prefix := strings.Join(addr, ".") + "."
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for k := range w.result {
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if strings.HasPrefix(k, prefix) {
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delete(w.result, k)
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}
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}
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}
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2015-01-10 20:44:26 +01:00
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func (w *MapFieldWriter) WriteField(addr []string, value interface{}) error {
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w.lock.Lock()
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defer w.lock.Unlock()
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if w.result == nil {
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w.result = make(map[string]string)
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}
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schemaList := addrToSchema(addr, w.Schema)
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if len(schemaList) == 0 {
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return fmt.Errorf("Invalid address to set: %#v", addr)
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}
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// If we're setting anything other than a list root or set root,
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// then disallow it.
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for _, schema := range schemaList[:len(schemaList)-1] {
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if schema.Type == TypeList {
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return fmt.Errorf(
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"%s: can only set full list",
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strings.Join(addr, "."))
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}
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if schema.Type == TypeMap {
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return fmt.Errorf(
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"%s: can only set full map",
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strings.Join(addr, "."))
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}
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if schema.Type == TypeSet {
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return fmt.Errorf(
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"%s: can only set full set",
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strings.Join(addr, "."))
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}
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}
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return w.set(addr, value)
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}
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func (w *MapFieldWriter) set(addr []string, value interface{}) error {
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schemaList := addrToSchema(addr, w.Schema)
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if len(schemaList) == 0 {
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return fmt.Errorf("Invalid address to set: %#v", addr)
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}
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schema := schemaList[len(schemaList)-1]
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switch schema.Type {
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2015-05-27 03:52:36 +02:00
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case TypeBool, TypeInt, TypeFloat, TypeString:
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2015-01-10 20:44:26 +01:00
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return w.setPrimitive(addr, value, schema)
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case TypeList:
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return w.setList(addr, value, schema)
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case TypeMap:
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return w.setMap(addr, value, schema)
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case TypeSet:
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return w.setSet(addr, value, schema)
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case typeObject:
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return w.setObject(addr, value, schema)
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default:
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panic(fmt.Sprintf("Unknown type: %#v", schema.Type))
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}
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}
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func (w *MapFieldWriter) setList(
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addr []string,
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v interface{},
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schema *Schema) error {
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k := strings.Join(addr, ".")
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setElement := func(idx string, value interface{}) error {
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addrCopy := make([]string, len(addr), len(addr)+1)
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copy(addrCopy, addr)
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return w.set(append(addrCopy, idx), value)
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}
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var vs []interface{}
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if err := mapstructure.Decode(v, &vs); err != nil {
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return fmt.Errorf("%s: %s", k, err)
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}
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helper/schema: Clear existing map/set/list contents before overwriting
There are situations where one may need to write to a set, list, or map
more than once per single TF operation (apply/refresh/etc). In these
cases, further writes using Set (example: d.Set("some_set", newSet))
currently create unstable results in the set writer (the name of the
writer layer that holds the data set by these calls) because old keys
are not being cleared out first.
This bug is most visible when using sets. Example: First write to set
writes elements that have been hashed at 10 and 20, and the second write
writes elements that have been hashed at 30 and 40. While the set length
has been correctly set at 2, since a set is basically a map (as is the
entire map writer) and map results are non-deterministic, reads to this
set will now deliver unstable results in a random but predictable
fashion as the map results are delivered to the caller non-deterministic
- sometimes you may correctly get 30 and 40, but sometimes you may get
10 and 20, or even 10 and 30, etc.
This problem propagates to state which is even more damaging as unstable
results are set to state where they become part of the permanent data
set going forward.
The problem also applies to lists and maps. This is probably more of an
issue with maps as a map can contain any key/value combination and hence
there is no predictable pattern where keys would be overwritten with
default or zero values. This is contrary to complex lists, which has
this problem as well, but since lists are deterministic and the length
of a list properly gets updated during the overwrite, the problem is
masked by the fact that a read will only read to the boundary of the
list, skipping any bad data that may still be available due past the
list boundary.
This update clears the child contents of any set, list, or map before
beginning a new write to address this issue. Tests are included for all
three data types.
2017-11-05 20:14:51 +01:00
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// Wipe the set from the current writer prior to writing if it exists.
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// Multiple writes to the same layer is a lot safer for lists than sets due
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// to the fact that indexes are always deterministic and the length will
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// always be updated with the current length on the last write, but making
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// sure we have a clean namespace removes any chance for edge cases to pop up
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// and ensures that the last write to the set is the correct value.
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w.clearTree(addr)
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2015-01-10 20:44:26 +01:00
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// Set the entire list.
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var err error
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for i, elem := range vs {
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is := strconv.FormatInt(int64(i), 10)
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err = setElement(is, elem)
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if err != nil {
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break
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}
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}
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if err != nil {
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for i, _ := range vs {
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is := strconv.FormatInt(int64(i), 10)
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setElement(is, nil)
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}
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return err
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}
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w.result[k+".#"] = strconv.FormatInt(int64(len(vs)), 10)
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return nil
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}
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func (w *MapFieldWriter) setMap(
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addr []string,
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value interface{},
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schema *Schema) error {
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k := strings.Join(addr, ".")
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v := reflect.ValueOf(value)
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vs := make(map[string]interface{})
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2015-05-06 17:21:22 +02:00
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if value == nil {
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2015-01-10 20:44:26 +01:00
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// The empty string here means the map is removed.
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w.result[k] = ""
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return nil
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}
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2015-05-06 17:21:22 +02:00
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if v.Kind() != reflect.Map {
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return fmt.Errorf("%s: must be a map", k)
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}
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if v.Type().Key().Kind() != reflect.String {
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return fmt.Errorf("%s: keys must strings", k)
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}
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for _, mk := range v.MapKeys() {
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mv := v.MapIndex(mk)
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vs[mk.String()] = mv.Interface()
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}
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helper/schema: Clear existing map/set/list contents before overwriting
There are situations where one may need to write to a set, list, or map
more than once per single TF operation (apply/refresh/etc). In these
cases, further writes using Set (example: d.Set("some_set", newSet))
currently create unstable results in the set writer (the name of the
writer layer that holds the data set by these calls) because old keys
are not being cleared out first.
This bug is most visible when using sets. Example: First write to set
writes elements that have been hashed at 10 and 20, and the second write
writes elements that have been hashed at 30 and 40. While the set length
has been correctly set at 2, since a set is basically a map (as is the
entire map writer) and map results are non-deterministic, reads to this
set will now deliver unstable results in a random but predictable
fashion as the map results are delivered to the caller non-deterministic
- sometimes you may correctly get 30 and 40, but sometimes you may get
10 and 20, or even 10 and 30, etc.
This problem propagates to state which is even more damaging as unstable
results are set to state where they become part of the permanent data
set going forward.
The problem also applies to lists and maps. This is probably more of an
issue with maps as a map can contain any key/value combination and hence
there is no predictable pattern where keys would be overwritten with
default or zero values. This is contrary to complex lists, which has
this problem as well, but since lists are deterministic and the length
of a list properly gets updated during the overwrite, the problem is
masked by the fact that a read will only read to the boundary of the
list, skipping any bad data that may still be available due past the
list boundary.
This update clears the child contents of any set, list, or map before
beginning a new write to address this issue. Tests are included for all
three data types.
2017-11-05 20:14:51 +01:00
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// Wipe this address tree. The contents of the map should always reflect the
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// last write made to it.
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w.clearTree(addr)
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2015-01-10 20:44:26 +01:00
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// Remove the pure key since we're setting the full map value
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delete(w.result, k)
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// Set each subkey
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addrCopy := make([]string, len(addr), len(addr)+1)
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copy(addrCopy, addr)
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for subKey, v := range vs {
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if err := w.set(append(addrCopy, subKey), v); err != nil {
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return err
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}
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}
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2015-01-15 23:12:24 +01:00
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// Set the count
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core: Use .% instead of .# for maps in state
The flatmapped representation of state prior to this commit encoded maps
and lists (and therefore by extension, sets) with a key corresponding to
the number of elements, or the unknown variable indicator under a .# key
and then individual items. For example, the list ["a", "b", "c"] would
have been encoded as:
listname.# = 3
listname.0 = "a"
listname.1 = "b"
listname.2 = "c"
And the map {"key1": "value1", "key2", "value2"} would have been encoded
as:
mapname.# = 2
mapname.key1 = "value1"
mapname.key2 = "value2"
Sets use the hash code as the key - for example a set with a (fictional)
hashcode calculation may look like:
setname.# = 2
setname.12312512 = "value1"
setname.56345233 = "value2"
Prior to the work done to extend the type system, this was sufficient
since the internal representation of these was effectively the same.
However, following the separation of maps and lists into distinct
first-class types, this encoding presents a problem: given a state file,
it is impossible to tell the encoding of an empty list and an empty map
apart. This presents problems for the type checker during interpolation,
as many interpolation functions will operate on only one of these two
structures.
This commit therefore changes the representation in state of maps to use
a "%" as the key for the number of elements. Consequently the map above
will now be encoded as:
mapname.% = 2
mapname.key1 = "value1"
mapname.key2 = "value2"
This has the effect of an empty list (or set) now being encoded as:
listname.# = 0
And an empty map now being encoded as:
mapname.% = 0
Therefore we can eliminate some nasty guessing logic from the resource
variable supplier for interpolation, at the cost of having to migrate
state up front (to follow in a subsequent commit).
In order to reduce the number of potential situations in which resources
would be "forced new", we continue to accept "#" as the count key when
reading maps via helper/schema. There is no situation under which we can
allow "#" as an actual map key in any case, as it would not be
distinguishable from a list or set in state.
2016-06-05 10:34:43 +02:00
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w.result[k+".%"] = strconv.Itoa(len(vs))
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2015-01-15 23:12:24 +01:00
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2015-01-10 20:44:26 +01:00
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return nil
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}
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func (w *MapFieldWriter) setObject(
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addr []string,
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value interface{},
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schema *Schema) error {
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// Set the entire object. First decode into a proper structure
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var v map[string]interface{}
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if err := mapstructure.Decode(value, &v); err != nil {
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return fmt.Errorf("%s: %s", strings.Join(addr, "."), err)
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}
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// Make space for additional elements in the address
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addrCopy := make([]string, len(addr), len(addr)+1)
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copy(addrCopy, addr)
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// Set each element in turn
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var err error
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for k1, v1 := range v {
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if err = w.set(append(addrCopy, k1), v1); err != nil {
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break
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}
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}
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if err != nil {
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for k1, _ := range v {
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w.set(append(addrCopy, k1), nil)
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}
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}
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return err
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}
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func (w *MapFieldWriter) setPrimitive(
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addr []string,
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v interface{},
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schema *Schema) error {
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k := strings.Join(addr, ".")
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if v == nil {
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2015-09-16 22:26:27 +02:00
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// The empty string here means the value is removed.
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w.result[k] = ""
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2015-01-10 20:44:26 +01:00
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return nil
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}
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var set string
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switch schema.Type {
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case TypeBool:
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var b bool
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if err := mapstructure.Decode(v, &b); err != nil {
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return fmt.Errorf("%s: %s", k, err)
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}
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set = strconv.FormatBool(b)
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case TypeString:
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if err := mapstructure.Decode(v, &set); err != nil {
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return fmt.Errorf("%s: %s", k, err)
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}
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case TypeInt:
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var n int
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if err := mapstructure.Decode(v, &n); err != nil {
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return fmt.Errorf("%s: %s", k, err)
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}
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2015-01-28 22:20:14 +01:00
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set = strconv.FormatInt(int64(n), 10)
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2015-01-28 18:53:34 +01:00
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case TypeFloat:
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|
|
var n float64
|
|
|
|
if err := mapstructure.Decode(v, &n); err != nil {
|
|
|
|
return fmt.Errorf("%s: %s", k, err)
|
|
|
|
}
|
2015-01-28 22:20:14 +01:00
|
|
|
set = strconv.FormatFloat(float64(n), 'G', -1, 64)
|
2015-01-10 20:44:26 +01:00
|
|
|
default:
|
|
|
|
return fmt.Errorf("Unknown type: %#v", schema.Type)
|
|
|
|
}
|
|
|
|
|
|
|
|
w.result[k] = set
|
|
|
|
return nil
|
|
|
|
}
|
|
|
|
|
|
|
|
func (w *MapFieldWriter) setSet(
|
|
|
|
addr []string,
|
|
|
|
value interface{},
|
|
|
|
schema *Schema) error {
|
|
|
|
addrCopy := make([]string, len(addr), len(addr)+1)
|
|
|
|
copy(addrCopy, addr)
|
2015-01-16 13:30:11 +01:00
|
|
|
k := strings.Join(addr, ".")
|
|
|
|
|
|
|
|
if value == nil {
|
|
|
|
w.result[k+".#"] = "0"
|
|
|
|
return nil
|
|
|
|
}
|
2015-01-10 20:44:26 +01:00
|
|
|
|
|
|
|
// If it is a slice, then we have to turn it into a *Set so that
|
|
|
|
// we get the proper order back based on the hash code.
|
|
|
|
if v := reflect.ValueOf(value); v.Kind() == reflect.Slice {
|
|
|
|
// Build a temp *ResourceData to use for the conversion
|
|
|
|
tempSchema := *schema
|
|
|
|
tempSchema.Type = TypeList
|
|
|
|
tempSchemaMap := map[string]*Schema{addr[0]: &tempSchema}
|
|
|
|
tempW := &MapFieldWriter{Schema: tempSchemaMap}
|
|
|
|
|
|
|
|
// Set the entire list, this lets us get sane values out of it
|
|
|
|
if err := tempW.WriteField(addr, value); err != nil {
|
|
|
|
return err
|
|
|
|
}
|
|
|
|
|
|
|
|
// Build the set by going over the list items in order and
|
|
|
|
// hashing them into the set. The reason we go over the list and
|
|
|
|
// not the `value` directly is because this forces all types
|
|
|
|
// to become []interface{} (generic) instead of []string, which
|
|
|
|
// most hash functions are expecting.
|
2016-01-21 21:54:56 +01:00
|
|
|
s := schema.ZeroValue().(*Set)
|
2015-01-10 20:44:26 +01:00
|
|
|
tempR := &MapFieldReader{
|
|
|
|
Map: BasicMapReader(tempW.Map()),
|
|
|
|
Schema: tempSchemaMap,
|
|
|
|
}
|
|
|
|
for i := 0; i < v.Len(); i++ {
|
|
|
|
is := strconv.FormatInt(int64(i), 10)
|
|
|
|
result, err := tempR.ReadField(append(addrCopy, is))
|
|
|
|
if err != nil {
|
|
|
|
return err
|
|
|
|
}
|
|
|
|
if !result.Exists {
|
|
|
|
panic("set item just set doesn't exist")
|
|
|
|
}
|
|
|
|
|
|
|
|
s.Add(result.Value)
|
|
|
|
}
|
|
|
|
|
|
|
|
value = s
|
|
|
|
}
|
|
|
|
|
helper/schema: Clear existing map/set/list contents before overwriting
There are situations where one may need to write to a set, list, or map
more than once per single TF operation (apply/refresh/etc). In these
cases, further writes using Set (example: d.Set("some_set", newSet))
currently create unstable results in the set writer (the name of the
writer layer that holds the data set by these calls) because old keys
are not being cleared out first.
This bug is most visible when using sets. Example: First write to set
writes elements that have been hashed at 10 and 20, and the second write
writes elements that have been hashed at 30 and 40. While the set length
has been correctly set at 2, since a set is basically a map (as is the
entire map writer) and map results are non-deterministic, reads to this
set will now deliver unstable results in a random but predictable
fashion as the map results are delivered to the caller non-deterministic
- sometimes you may correctly get 30 and 40, but sometimes you may get
10 and 20, or even 10 and 30, etc.
This problem propagates to state which is even more damaging as unstable
results are set to state where they become part of the permanent data
set going forward.
The problem also applies to lists and maps. This is probably more of an
issue with maps as a map can contain any key/value combination and hence
there is no predictable pattern where keys would be overwritten with
default or zero values. This is contrary to complex lists, which has
this problem as well, but since lists are deterministic and the length
of a list properly gets updated during the overwrite, the problem is
masked by the fact that a read will only read to the boundary of the
list, skipping any bad data that may still be available due past the
list boundary.
This update clears the child contents of any set, list, or map before
beginning a new write to address this issue. Tests are included for all
three data types.
2017-11-05 20:14:51 +01:00
|
|
|
// Clear any keys that match the set address first. This is necessary because
|
|
|
|
// it's always possible and sometimes may be necessary to write to a certain
|
|
|
|
// writer layer more than once with different set data each time, which will
|
|
|
|
// lead to different keys being inserted, which can lead to determinism
|
|
|
|
// problems when the old data isn't wiped first.
|
|
|
|
w.clearTree(addr)
|
|
|
|
|
2015-01-16 12:43:57 +01:00
|
|
|
for code, elem := range value.(*Set).m {
|
2015-11-18 11:24:04 +01:00
|
|
|
if err := w.set(append(addrCopy, code), elem); err != nil {
|
2015-01-16 12:43:57 +01:00
|
|
|
return err
|
2015-01-10 20:44:26 +01:00
|
|
|
}
|
|
|
|
}
|
2015-01-16 12:43:57 +01:00
|
|
|
|
|
|
|
w.result[k+".#"] = strconv.Itoa(value.(*Set).Len())
|
2015-01-10 20:44:26 +01:00
|
|
|
return nil
|
|
|
|
}
|