Debezium connector for Db2
|
This connector is in an incubating state. Exact semantics, configuration options and other features may change in future revisions, based on the feedback we receive. Please let us know if you encounter any problems. |
Debezium’s Db2 connector can capture row-level changes in the tables of a Db2 database. This connector is strongly inspired by the Debezium implementation of SQL Server, which uses a SQL-based polling model that puts tables into "capture mode". When a table is in capture mode, the Debezium Db2 connector generates and streams a change event for each row-level update to that table.
A table that is in capture mode has an associated change-data table, which Db2 creates. For each change to a table that is in capture mode, Db2 adds data about that change to the table’s associated change-data table. A change-data table contains an entry for each state of a row. It also has special entries for deletions. The Debezium Db2 connector reads change events from change-data tables and emits the events to Kafka topics.
The first time a Debezium Db2 connector connects to a Db2 database, the connector reads a consistent snapshot of the tables for which the connector is configured to capture changes. By default, this is all non-system tables. There are connector configuration properties that let you specify which tables to put into capture mode, or which tables to exclude from capture mode.
When the snapshot is complete the connector begins emitting change events for committed updates to tables that are in capture mode. By default, change events for a particular table go to a Kafka topic that has the same name as the table. Applications and services consume change events from these topics.
The connector uses the abstract syntax notation (ASN) libraries that come as a standard part of Db2 LUW (Db2 for Linux, UNIX and Windows) and which you can add to Db2 zOS. To use ASN and hence this connector, you must have a license for the IBM InfoSphere Data Replication (IIDR) product. However, IIDR does not need to be installed.
The Db2 connector has been tested with Db2/Linux <IP_ADDRESS>. It is expected that the connector would also work on Windows, AIX and zOS.
Overview
The Debezium Db2 connector is based on the ASN Capture/Apply agents that enable SQL Replication in Db2. A capture agent:
-
Generates change-data tables for tables that are in capture mode.
-
Monitors tables in capture mode and stores change events for updates to those tables in their corresponding change-data tables.
The Debezium connector uses a SQL interface to query change-data tables for change events.
The database administrator must put the tables for which you want to capture changes into capture mode. For convenience and for automating testing, there are Debezium user-defined functions (UDFs) in C that you can compile and then use to do the following management tasks:
-
Start, stop, and reinitialize the ASN agent
-
Put tables into capture mode
-
Create the replication (ASN) schemas and change-data tables
-
Remove tables from capture mode
Alternatively, you can use Db2 control commands to accomplish these tasks.
After the tables of interest are in capture mode, the connector reads their corresponding change-data tables to obtain change events for table updates. The connector emits a change event for each row-level insert, update, and delete operation to a Kafka topic that has the same name as the changed table. This is default behavior that you can modify. Client applications read the Kafka topics that correspond to the database tables of interest and can react to each row-level change event.
Typically, the database administrator puts a table into capture mode in the middle of the life of a table. This means that the connector does not have the complete history of all changes that have been made to the table. Therefore, when the Db2 connector first connects to a particular Db2 database, it starts by performing a consistent snapshot of each table that is in capture mode. After the connector completes the snapshot, the connector streams change events from the point at which the snapshot was made. In this way, the connector starts with a consistent view of the tables that are in capture mode, and does not drop any changes that were made while it was performing the snapshot.
Debezium connectors are tolerant of failures. As the connector reads and produces change events, it records the log sequence number (LSN) of the change-data table entry. The LSN is the position of the change event in the database log. If the connector stops for any reason, including communication failures, network problems, or crashes, upon restarting it continues reading the change-data tables where it left off. This includes snapshots. That is, if the snapshot was not complete when the connector stopped, upon restart the connector begins a new snapshot.
How the connector works
To optimally configure and run a Debezium Db2 connector, it is helpful to understand how the connector performs snapshots, streams change events, determines Kafka topic names, and handles schema changes.
Snapshots
Db2`s replication feature is not designed to store the complete history of database changes. Consequently, when a Debezium Db2 connector connects to a database for the first time, it takes a consistent snapshot of tables that are in capture mode and streams this state to Kafka. This establishes the baseline for table content.
By default, when a Db2 connector performs a snapshot, it does the following:
-
Determines which tables are in capture mode, and thus must be included in the snapshot. By default, all non-system tables are in capture mode. Connector configuration properties, such as
table.exclude.list
andtable.include.list
let you specify which tables should be in capture mode. -
Obtains a lock on each of the tables in capture mode. This ensures that no schema changes can occur in those tables during the snapshot. The level of the lock is determined by the
snapshot.isolation.mode
connector configuration property. -
Reads the highest (most recent) LSN position in the server’s transaction log.
-
Captures the schema of all tables that are in capture mode. The connector persists this information in its internal database history topic.
-
Optional, releases the locks obtained in step 2. Typically, these locks are held for only a short time.
-
At the LSN position read in step 3, the connector scans the capture mode tables as well as their schemas. During the scan, the connector:
-
Confirms that the table was created before the start of the snapshot. If it was not, the snapshot skips that table. After the snapshot is complete, and the connector starts emitting change events, the connector produces change events for any tables that were created during the snapshot.
-
Produces a read event for each row in each table that is in capture mode. All read events contain the same LSN position, which is the LSN position that was obtained in step 3.
-
Emits each read event to the Kafka topic that has the same name as the table.
-
-
Records the successful completion of the snapshot in the connector offsets.
Change-data tables
After a complete snapshot, when a Debezium Db2 connector starts for the first time, the connector identifies the change-data table for each source table that is in capture mode. The connector does the following for each change-data table:
-
Reads change events that were created between the last stored, highest LSN and the current, highest LSN.
-
Orders the change events according to the commit LSN and the change LSN for each event. This ensures that the connector emits the change events in the order in which the table changes occurred.
-
Passes commit and change LSNs as offsets to Kafka Connect.
-
Stores the highest LSN that the connector passed to Kafka Connect.
After a restart, the connector resumes emitting change events from the offset (commit and change LSNs) where it left off. While the connector is running and emitting change events, if you remove a table from capture mode or add a table to capture mode, the connector detects this and modifies its behavior accordingly.
Topic names
By default, the Db2 connector writes change events for all insert, update, and delete operations on a single table to a single Kafka topic. The name of the Kafka topic has the following format:
databaseName.schemaName.tableName
- databaseName
-
The logical name of the connector as specified with the
database.server.name
connector configuration property. - schemaName
-
The name of the schema in which the operation occurred.
- tableName
-
The name of the table in which the operation occurred.
For example, consider a Db2 installation with the mydatabase
database, which contains four tables: PRODUCTS
, PRODUCTS_ON_HAND
, CUSTOMERS
, and ORDERS
that are in the MYSCHEMA
schema. The connector would emit events to these four Kafka topics:
-
mydatabase.MYSCHEMA.PRODUCTS
-
mydatabase.MYSCHEMA.PRODUCTS_ON_HAND
-
mydatabase.MYSCHEMA.CUSTOMERS
-
mydatabase.MYSCHEMA.ORDERS
To configure a Db2 connector to emit change events to differently-named Kafka topics, see the documentation for the topic routing transformation.
Schema change topic
For a table that is in capture mode, the Debezium Db2 connector stores the history of schema changes to that table in a database history topic. This topic reflects an internal connector state and you should not use it. If your application needs to track schema changes, there is a public schema change topic. The name of the schema change topic is the same as the logical server name specified in the connector configuration.
|
The format of messages that a connector emits to its schema change topic is in an incubating state and can change without notice. |
Debezium emits a message to the schema change topic when:
-
A new table goes into capture mode.
-
A table is removed from capture mode.
-
During a database schema update, there is a change in the schema for a table that is in capture mode.
A message to the schema change topic contains a logical representation of the table schema, for example:
{
"schema": {
...
},
"payload": {
"source": {
"version": "1.3.1.Final",
"connector": "db2",
"name": "db2",
"ts_sec":<PHONE_NUMBER>953,
"snapshot": "true",
"db": "testdb",
"schema": "DB2INST1",
"table": "CUSTOMERS",
"change_lsn": null,
"commit_lsn": "00000025:00000d98:00a2",
"event_serial_no": null
},
"databaseName": "TESTDB", (1)
"schemaName": "DB2INST1",
"ddl": null, (2)
"tableChanges": [ (3)
{
"type": "CREATE", (4)
"id": "\"DB2INST1\".\"CUSTOMERS\"", (5)
"table": { (6)
"defaultCharsetName": null,
"primaryKeyColumnNames": [ (7)
"ID"
],
"columns": [ (8)
{
"name": "ID",
"jdbcType": 4,
"nativeType": null,
"typeName": "int identity",
"typeExpression": "int identity",
"charsetName": null,
"length": 10,
"scale": 0,
"position": 1,
"optional": false,
"autoIncremented": false,
"generated": false
},
{
"name": "FIRST_NAME",
"jdbcType": 12,
"nativeType": null,
"typeName": "varchar",
"typeExpression": "varchar",
"charsetName": null,
"length": 255,
"scale": null,
"position": 2,
"optional": false,
"autoIncremented": false,
"generated": false
},
{
"name": "LAST_NAME",
"jdbcType": 12,
"nativeType": null,
"typeName": "varchar",
"typeExpression": "varchar",
"charsetName": null,
"length": 255,
"scale": null,
"position": 3,
"optional": false,
"autoIncremented": false,
"generated": false
},
{
"name": "EMAIL",
"jdbcType": 12,
"nativeType": null,
"typeName": "varchar",
"typeExpression": "varchar",
"charsetName": null,
"length": 255,
"scale": null,
"position": 4,
"optional": false,
"autoIncremented": false,
"generated": false
}
]
}
}
]
}
}
| Item | Field name | Description |
|---|---|---|
1 |
|
Identifies the database and the schema that contain the change. |
2 |
|
Always |
3 |
|
An array of one or more items that contain the schema changes generated by a DDL command. |
4 |
|
Describes the kind of change. The value is one of the following:
|
5 |
|
Full identifier of the table that was created, altered, or dropped. |
6 |
|
Represents table metadata after the applied change. |
7 |
|
List of columns that compose the table’s primary key. |
8 |
|
Metadata for each column in the changed table. |
In messages to the schema change topic, the key is the name of the database that contains the schema change. In the following example, the payload
field contains the key:
{
"schema": {
"type": "struct",
"fields": [
{
"type": "string",
"optional": false,
"field": "databaseName"
}
],
"optional": false,
"name": "io.debezium.connector.db2.SchemaChangeKey"
},
"payload": {
"databaseName": "TESTDB"
}
}
Transaction metadata
Debezium can generate events that represent transaction boundaries and that enrich change data event messages. For every transaction BEGIN
and END
, Debezium generates an event that contains the following fields:
-
status
-BEGIN
orEND
-
id
- string representation of unique transaction identifier -
event_count
(forEND
events) - total number of events emitted by the transaction -
data_collections
(forEND
events) - an array of pairs ofdata_collection
andevent_count
that provides the number of events emitted by changes originating from the given data collection
{
"status": "BEGIN",
"id": "00000025:00000d08:0025",
"event_count": null,
"data_collections": null
}
{
"status": "END",
"id": "00000025:00000d08:0025",
"event_count": 2,
"data_collections": [
{
"data_collection": "testDB.dbo.tablea",
"event_count": 1
},
{
"data_collection": "testDB.dbo.tableb",
"event_count": 1
}
]
}
The connector emits transaction events to the database.server.name.transaction
topic.
When transaction metadata is enabled the connector enriches the change event Envelope
with a new transaction
field.
This field provides information about every event in the form of a composite of fields:
-
id
- string representation of unique transaction identifier -
total_order
- absolute position of the event among all events generated by the transaction -
data_collection_order
- the per-data collection position of the event among all events that were emitted by the transaction
Following is an example of a message:
{
"before": null,
"after": {
"pk": "2",
"aa": "1"
},
"source": {
...
},
"op": "c",
"ts_ms": "1580390884335",
"transaction": {
"id": "00000025:00000d08:0025",
"total_order": "1",
"data_collection_order": "1"
}
}
Data change events
The Debezium Db2 connector generates a data change event for each row-level INSERT
, UPDATE
, and DELETE
operation. Each event contains a key and a value. The structure of the key and the value depends on the table that was changed.
Debezium and Kafka Connect are designed around continuous streams of event messages. However, the structure of these events may change over time, which can be difficult for consumers to handle. To address this, each event contains the schema for its content or, if you are using a schema registry, a schema ID that a consumer can use to obtain the schema from the registry. This makes each event self-contained.
The following skeleton JSON shows the basic four parts of a change event. However, how you configure the Kafka Connect converter that you choose to use in your application determines the representation of these four parts in change events. A schema
field is in a change event only when you configure the converter to produce it. Likewise, the event key and event payload are in a change event only if you configure a converter to produce it. If you use the JSON converver and you configure it to produce all four basic change event parts, change events have this structure:
{
"schema": { (1)
...
},
"payload": { (2)
...
},
"schema": { (3)
...
},
"payload": { (4)
...
},
}
| Item | Field name | Description |
|---|---|---|
1 |
|
The first |
2 |
|
The first |
3 |
|
The second |
4 |
|
The second |
By default, the connector streams change event records to topics with names that are the same as the event’s originating table. See topic names.
|
The Debezium Db2 connector ensures that all Kafka Connect schema names adhere to the Avro schema name format. This means that the logical server name must start with a Latin letter or an underscore, that is, a-z, A-Z, or _. Each remaining character in the logical server name and each character in the database and table names must be a Latin letter, a digit, or an underscore, that is, a-z, A-Z, 0-9, or \_. If there is an invalid character it is replaced with an underscore character. This can lead to unexpected conflicts if the logical server name, a database name, or a table name contains invalid characters, and the only characters that distinguish names from one another are invalid and thus replaced with underscores. Also, Db2 names for databases, schemas, and tables can be case sensitive. This means that the connector could emit event records for more than one table to the same Kafka topic. |
Change event keys
A change event’s key contains the schema for the changed table’s key and the changed row’s actual key. Both the schema and its corresponding payload contain a field for each column in the changed table’s PRIMARY KEY
(or unique constraint) at the time the connector created the event.
Consider the following customers
table, which is followed by an example of a change event key for this table.
CREATE TABLE customers (
ID INTEGER IDENTITY(1001,1) NOT NULL PRIMARY KEY,
FIRST_NAME VARCHAR(255) NOT NULL,
LAST_NAME VARCHAR(255) NOT NULL,
EMAIL VARCHAR(255) NOT NULL UNIQUE
);
Every change event that captures a change to the customers
table has the same event key schema. For as long as the customers
table has the previous definition, every change event that captures a change to the customers
table has the following key structure. In JSON, it looks like this:
{
"schema": { (1)
"type": "struct",
"fields": [ (2)
{
"type": "int32",
"optional": false,
"field": "ID"
}
],
"optional": false, (3)
"name": "mydatabase.MYSCHEMA.CUSTOMERS.Key" (4)
},
"payload": { (5)
"ID": 1004
}
}
| Item | Field name | Description |
|---|---|---|
1 |
|
The schema portion of the key specifies a Kafka Connect schema that describes what is in the key’s |
2 |
|
Specifies each field that is expected in the |
3 |
|
Indicates whether the event key must contain a value in its |
4 |
|
Name of the schema that defines the structure of the key’s payload. This schema describes the structure of the primary key for the table that was changed. Key schema names have the format connector-name.database-name.table-name.
|
5 |
|
Contains the key for the row for which this change event was generated. In this example, the key, contains a single |
Change event values
The value in a change event is a bit more complicated than the key. Like the key, the value has a schema
section and a payload
section. The schema
section contains the schema that describes the Envelope
structure of the payload
section, including its nested fields. Change events for operations that create, update or delete data all have a value payload with an envelope structure.
Consider the same sample table that was used to show an example of a change event key:
CREATE TABLE customers (
ID INTEGER IDENTITY(1001,1) NOT NULL PRIMARY KEY,
FIRST_NAME VARCHAR(255) NOT NULL,
LAST_NAME VARCHAR(255) NOT NULL,
EMAIL VARCHAR(255) NOT NULL UNIQUE
);
The event value portion of every change event for the customers
table specifies the same schema. The event value’s payload varies according to the event type:
create events
The following example shows the value portion of a change event that the connector generates for an operation that creates data in the customers
table:
{
"schema": { (1)
"type": "struct",
"fields": [
{
"type": "struct",
"fields": [
{
"type": "int32",
"optional": false,
"field": "ID"
},
{
"type": "string",
"optional": false,
"field": "FIRST_NAME"
},
{
"type": "string",
"optional": false,
"field": "LAST_NAME"
},
{
"type": "string",
"optional": false,
"field": "EMAIL"
}
],
"optional": true,
"name": "mydatabase.MYSCHEMA.CUSTOMERS.Value", (2)
"field": "before"
},
{
"type": "struct",
"fields": [
{
"type": "int32",
"optional": false,
"field": "ID"
},
{
"type": "string",
"optional": false,
"field": "FIRST_NAME"
},
{
"type": "string",
"optional": false,
"field": "LAST_NAME"
},
{
"type": "string",
"optional": false,
"field": "EMAIL"
}
],
"optional": true,
"name": "mydatabase.MYSCHEMA.CUSTOMERS.Value",
"field": "after"
},
{
"type": "struct",
"fields": [
{
"type": "string",
"optional": false,
"field": "version"
},
{
"type": "string",
"optional": false,
"field": "connector"
},
{
"type": "string",
"optional": false,
"field": "name"
},
{
"type": "int64",
"optional": false,
"field": "ts_sec"
},
{
"type": "boolean",
"optional": true,
"default": false,
"field": "snapshot"
},
{
"type": "string",
"optional": false,
"field": "db"
},
{
"type": "string",
"optional": false,
"field": "schema"
},
{
"type": "string",
"optional": false,
"field": "table"
},
{
"type": "string",
"optional": true,
"field": "change_lsn"
},
{
"type": "string",
"optional": true,
"field": "commit_lsn"
},
],
"optional": false,
"name": "io.debezium.connector.db2.Source", (3)
"field": "source"
},
{
"type": "string",
"optional": false,
"field": "op"
},
{
"type": "int64",
"optional": true,
"field": "ts_ms"
}
],
"optional": false,
"name": "mydatabase.MYSCHEMA.CUSTOMERS.Envelope" (4)
},
"payload": { (5)
"before": null, (6)
"after": { (7)
"ID": 1005,
"FIRST_NAME": "john",
"LAST_NAME": "doe",
"EMAIL"<EMAIL_ADDRESS>},
"source": { (8)
"version": "1.3.1.Final",
"connector": "db2",
"name": "myconnector",
"ts_sec":<PHONE_NUMBER>470,
"snapshot": false,
"db": "mydatabase",
"schema": "MYSCHEMA",
"table": "CUSTOMERS",
"change_lsn": "00000027:00000758:0003",
"commit_lsn": "00000027:00000758:0005",
},
"op": "c", (9)
"ts_ms":<PHONE_NUMBER>739 (10)
}
}
| Item | Field name | Description |
|---|---|---|
1 |
|
The value’s schema, which describes the structure of the value’s payload. A change event’s value schema is the same in every change event that the connector generates for a particular table. |
2 |
|
In the |
3 |
|
|
4 |
|
|
5 |
|
The value’s actual data. This is the information that the change event is providing. |
6 |
|
An optional field that specifies the state of the row before the event occurred. When the |
7 |
|
An optional field that specifies the state of the row after the event occurred. In this example, the |
8 |
|
Mandatory field that describes the source metadata for the event. The
|
9 |
|
Mandatory string that describes the type of operation that caused the connector to generate the event. In this example,
|
10 |
|
Optional field that displays the time at which the connector processed the event. The time is based on the system clock in the JVM running the Kafka Connect task. |
update events
The value of a change event for an update in the sample customers
table has the same schema as a create event for that table. Likewise, the update event value’s payload has the same structure. However, the event value payload contains different values in an update event. Here is an example of a change event value in an event that the connector generates for an update in the customers
table:
{
"schema": { ... },
"payload": {
"before": { (1)
"ID": 1005,
"FIRST_NAME": "john",
"LAST_NAME": "doe",
"EMAIL"<EMAIL_ADDRESS>},
"after": { (2)
"ID": 1005,
"FIRST_NAME": "john",
"LAST_NAME": "doe",
"EMAIL"<EMAIL_ADDRESS>},
"source": { (3)
"version": "1.3.1.Final",
"connector": "db2",
"name": "myconnector",
"ts_sec":<PHONE_NUMBER>937,
"snapshot": false,
"db": "mydatabase",
"schema": "MYSCHEMA",
"table": "CUSTOMERS",
"change_lsn": "00000027:00000ac0:0002",
"commit_lsn": "00000027:00000ac0:0007",
},
"op": "u", (4)
"ts_ms":<PHONE_NUMBER>706 (5)
}
}
| Item | Field name | Description |
|---|---|---|
1 |
|
An optional field that specifies the state of the row before the event occurred. In an update event value, the |
2 |
|
An optional field that specifies the state of the row after the event occurred. You can compare the |
3 |
|
Mandatory field that describes the source metadata for the event. The
|
4 |
|
Mandatory string that describes the type of operation. In an update event value, the |
5 |
|
Optional field that displays the time at which the connector processed the event. The time is based on the system clock in the JVM running the Kafka Connect task. |
|
Updating the columns for a row’s primary/unique key changes the value of the row’s key. When a key changes, Debezium outputs three events: a |
delete events
The value in a delete change event has the same schema
portion as create and update events for the same table. The event value payload
in a delete event for the sample customers
table looks like this:
{
"schema": { ... },
},
"payload": {
"before": { (1)
"ID": 1005,
"FIRST_NAME": "john",
"LAST_NAME": "doe",
"EMAIL"<EMAIL_ADDRESS>},
"after": null, (2)
"source": { (3)
"version": "1.3.1.Final",
"connector": "db2",
"name": "myconnector",
"ts_sec":<PHONE_NUMBER>243,
"snapshot": false,
"db": "mydatabase",
"schema": "MYSCHEMA",
"table": "CUSTOMERS",
"change_lsn": "00000027:00000db0:0005",
"commit_lsn": "00000027:00000db0:0007"
},
"op": "d", (4)
"ts_ms":<PHONE_NUMBER>205 (5)
}
}
| Item | Field name | Description |
|---|---|---|
1 |
|
Optional field that specifies the state of the row before the event occurred. In a delete event value, the |
2 |
|
Optional field that specifies the state of the row after the event occurred. In a delete event value, the |
3 |
|
Mandatory field that describes the source metadata for the event. In a delete event value, the
|
4 |
|
Mandatory string that describes the type of operation. The |
5 |
|
Optional field that displays the time at which the connector processed the event. The time is based on the system clock in the JVM running the Kafka Connect task. |
A delete change event record provides a consumer with the information it needs to process the removal of this row. The old values are included because some consumers might require them in order to properly handle the removal.
Db2 connector events are designed to work with Kafka log compaction. Log compaction enables removal of some older messages as long as at least the most recent message for every key is kept. This lets Kafka reclaim storage space while ensuring that the topic contains a complete data set and can be used for reloading key-based state.
When a row is deleted, the delete event value still works with log compaction, because Kafka can remove all earlier messages that have that same key. However, for Kafka to remove all messages that have that same key, the message value must be null
. To make this possible, after Debezium’s Db2 connector emits a delete event, the connector emits a special tombstone event that has the same key but a null
value.
Data type mappings
Db2’s data types are described in Db2 SQL Data Types.
The Db2 connector represents changes to rows with events that are structured like the table in which the row exists. The event contains a field for each column value. How that value is represented in the event depends on the Db2 data type of the column. This section describes these mappings.
Basic types
The following table describes how the connector maps each of the Db2 data types to a literal type and a semantic type in event fields.
-
literal type describes how the value is represented using Kafka Connect schema types:
INT8
,INT16
,INT32
,INT64
,FLOAT32
,FLOAT64
,BOOLEAN
,STRING
,BYTES
,ARRAY
,MAP
, andSTRUCT
. -
semantic type describes how the Kafka Connect schema captures the meaning of the field using the name of the Kafka Connect schema for the field.
| Db2 data type | Literal type (schema type) | Semantic type (schema name) and Notes |
|---|---|---|
|
|
Only snapshots can be taken from tables with BOOLEAN type columns. Currently SQL Replication on Db2 does not support BOOLEAN, so Debezium can not perform CDC on those tables.  Change events contain the field’s default value unless an explicit column value had been given. Consequently, there is rarely a need to obtain the default value from the schema. Passing the default value helps satisfy compatibility rules when using Avro as the serialization format together with the Confluent schema registry.
Temporal types
Other than Db2’s DATETIMEOFFSET
data type, which contains time zone information, how temporal types are mapped depends on the value of the time.precision.mode
connector configuration property. The following sections describe these mappings:
time.precision.mode=adaptive
When the time.precision.mode
configuration property is set to adaptive
, the default, the connector determines the literal type and semantic type based on the column’s data type definition. This ensures that events exactly represent the values in the database.
| Db2 data type | Literal type (schema type) | Semantic type (schema name) and Notes |
|---|---|---|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
time.precision.mode=connect
When the time.precision.mode
configuration property is set to connect
, the connector uses Kafka Connect logical types. This may be useful when consumers can handle only the built-in Kafka Connect logical types and are unable to handle variable-precision time values. However, since Db2 supports tenth of a microsecond precision, the events generated by a connector with the connect
time precision results in a loss of precision when the database column has a fractional second precision value that is greater than 3.
| Db2 data type | Literal type (schema type) | Semantic type (schema name) and Notes |
|---|---|---|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Timestamp types
The DATETIME
, SMALLDATETIME
and DATETIME2
types represent a timestamp without time zone information.
Such columns are converted into an equivalent Kafka Connect value based on UTC. For example, the DATETIME2
value "2018-06-20 15:13:16.945104" is represented by an io.debezium.time.MicroTimestamp
with the value "1529507596945104".
The timezone of the JVM running Kafka Connect and Debezium does not affect this conversion.
Decimal types
| Db2 data type | Literal type (schema type) | Semantic type (schema name) and Notes |
|---|---|---|
|
|
|
|
|
|
|
|
|
|
|
|
Set up
A database administrator must put tables into capture mode before you can run a Debezium Db2 connector to capture changes that are committed to a Db2 database. To put tables into capture mode, Debezium provides a set of user-defined functions (UDFs) for your convenience. The procedure here shows how to install and run these management UDFs. Alternatively, you can run Db2 control commands to put tables into capture mode.
This procedure assumes that you are logged in as the db2instl
user, which is the default instance and user name when using the Db2 docker container image.
-
On the machine on which Db2 is running, the content in
debezium-connector-db2/src/test/docker/db2-cdc-docker
is available in the$HOME/asncdctools/src
directory.
-
Compile the Debezium management UDFs on the Db2 server host by using the
bldrtn
command provided with Db2:cd $HOME/asncdctools/src
./bldrtn asncdc
-
Start the database if it is not already running. Replace
DB_NAME
with the name of the database that you want Debezium to connect to.db2 start db DB_NAME
-
Ensure that JDBC can read the Db2 metadata catalog:
cd $HOME/sqllib/bnd
db2 bind db2schema.bnd blocking all grant public sqlerror continue
-
Ensure that the database was recently backed-up. The ASN agents must have a recent starting point to read from. If you need to perform a backup, run the following commands, which prune the data so that only the most recent version is available. If you do not need to retain the older versions of the data, specify
dev/null
for the backup location.-
Back up the database. Replace
DB_NAME
andBACK_UP_LOCATION
with appropriate values:db2 backup db DB_NAME to BACK_UP_LOCATION
-
Restart the database:
db2 restart db DB_NAME
-
-
Connect to the database to install the Debezium management UDFs. It is assumed that you are logged in as the
db2instl
user so the UDFs should be installed on thedb2inst1
user.db2 connect to DB_NAME
-
Copy the Debezium management UDFs and set permissions for them:
cp $HOME/asncdctools/src/asncdc $HOME/sqllib/function
chmod 777 $HOME/sqllib/function
-
Enable the Debezium UDF that starts and stops the ASN capture agent:
db2 -tvmf $HOME/asncdctools/src/asncdc_UDF.sql
-
Create the ASN control tables:
$ db2 -tvmf $HOME/asncdctools/src/asncdctables.sql
-
Enable the Debezium UDF that adds tables to capture mode and removes tables from capture mode:
$ db2 -tvmf $HOME/asncdctools/src/asncdcaddremove.sql
After you set up the Db2 server, use the UDFs to control Db2 replication (ASN) with SQL commands. Some of the UDFs expect a return value in which case you use the SQL
VALUE
statement to invoke them. For other UDFs, use the SQLCALL
statement. -
Start the ASN agent:
VALUES ASNCDC.ASNCDCSERVICES('start','asncdc');
-
Put tables into capture mode. Invoke the following statement for each table that you want to put into capture. Replace
MYSCHEMA
with the name of the schema that contains the table you want to put into capture mode. Likewise, replaceMYTABLE
with the name of the table to put into capture mode:CALL ASNCDC.ADDTABLE('MYSCHEMA', 'MYTABLE');
-
Reinitialize the ASN service:
VALUES ASNCDC.ASNCDCSERVICES('reinit','asncdc');
Deployment
With Zookeeper, Kafka, and Kafka Connect installed, the remaining tasks to deploy a Debezium Db2 connector are:
-
Download the connector’s plug-in archive.
-
Extract the JAR files into your Kafka Connect environment.
-
Add the directory with the JAR files to Kafka Connect’s
plugin.path
. -
Obtain the JDBC driver for Db2.
-
Add the JDBC driver JAR file to the directory with the Debezium Db2 connector JARs.
-
Configure the connector and add the configuration to your Kafka Connect cluster.
-
Restart your Kafka Connect process to pick up the new JAR files.
If you are working with immutable containers, see Debezium’s Container images for Zookeeper, Kafka and Kafka Connect with the Db2 connector already installed and ready to run. You can also run Debezium on Kubernetes and OpenShift.
Connector configuration example
Following is an example of the configuration for a Db2 connector that connects to a Db2 server on port 50000 at <IP_ADDRESS>, whose logical name is fullfillment
. Typically, you configure the Debezium Db2 connector in a .json
file using the configuration properties available for the connector.
You can choose to produce events for a subset of the schemas and tables. Optionally, ignore, mask, or truncate columns that are sensitive, too large, or not needed.
{
"name": "db2-connector", (1)
"config": {
"connector.class": "io.debezium.connector.db2.Db2Connector", (2)
"database.hostname": "<IP_ADDRESS>", (3)
"database.port": "50000", (4)
"database.user": "db2inst1", (5)
"database.password": "Password!", (6)
"database.dbname": "mydatabase", (7)
"database.server.name": "fullfillment", (8)
"table.include.list": "MYSCHEMA.CUSTOMERS", (9)
"database.history.kafka.bootstrap.servers": "kafka:9092", (10)
"database.history.kafka.topic": "dbhistory.fullfillment" (11)
}
}
| 1 | The name of the connector when registered with a Kafka Connect service. |
| 2 | The name of this Db2 connector class. |
| 3 | The address of the Db2 instance. |
| 4 | The port number of the Db2 instance. |
| 5 | The name of the Db2 user. |
| 6 | The password for the Db2 user. |
| 7 | The name of the database to capture changes from. |
| 8 | The logical name of the Db2 instance/cluster, which forms a namespace and is used in all the names of the Kafka topics to which the connector writes, the Kafka Connect schema names, and the namespaces of the corresponding Avro schema when the Avro Connector is used. |
| 9 | A list of all tables whose changes Debezium should capture. |
| 10 | The list of Kafka brokers that this connector uses to write and recover DDL statements to the database history topic. |
| 11 | The name of the database history topic where the connector writes and recovers DDL statements. This topic is for internal use only and should not be used by consumers. |
See the complete list of connector properties that you can specify in these configurations.
You can send this configuration with a POST
command to a running Kafka Connect service. The service records the configuration and starts one connector task that connects to the Db2 database, reads change-data tables for tables in capture mode, and streams change event records to Kafka topics.
Adding connector configuration
To start running a Db2 connector, create a connector configuration and add the configuration to your Kafka Connect cluster.
-
The Db2 replication is enabled to expose change-data for tables that are in capture mode
-
The Db2 connector is installed.
-
Create a configuration for the Db2 connector.
-
Use the Kafka Connect REST API to add that connector configuration to your Kafka Connect cluster.
When the connector starts, it performs a consistent snapshot of the Db2 database tables that the connector is configured to capture changes for. The connector then starts generating data change events for row-level operations and streaming change event records to Kafka topics.
Connector properties
The Debezium Db2 connector has numerous configuration properties that you can use to achieve the right connector behavior for your application. Many properties have default values. Information about the properties is organized as follows:
The following configuration properties are required unless a default value is available.
| Property | Default | Description |
|---|---|---|
Unique name for the connector. Attempting to register again with the same name will fail. This property is required by all Kafka Connect connectors. |
||
The name of the Java class for the connector. Always use a value of |
||
|
The maximum number of tasks that should be created for this connector. The Db2 connector always uses a single task and therefore does not use this value, so the default is always acceptable. |
|
IP address or hostname of the Db2 database server. |
||
|
Integer port number of the Db2 database server. |
|
Name of the Db2 database user for connecting to the Db2 database server. |
||
Password to use when connecting to the Db2 database server. |
||
The name of the Db2 database from which to stream the changes |
||
Logical name that identifies and provides a namespace for the particular Db2 database server that hosts the database for which Debezium is capturing changes. Only alphanumeric characters and underscores should be used in the database server logical name. The logical name should be unique across all other connectors, since it is used as a topic name prefix for all Kafka topics that receive records from this connector. |
||
The full name of the Kafka topic where the connector stores the database schema history. |
||
A list of host/port pairs that the connector uses to establish an initial connection to the Kafka cluster. This connection is used for retrieving database schema history previously stored by the connector, and for writing each DDL statement read from the source database. Each pair should point to the same Kafka cluster used by the Debezium Kafka Connect process. |
||
An optional, comma-separated list of regular expressions that match fully-qualified table identifiers for tables whose changes you want the connector to capture. Any table not included in the include list does not have its changes captured. Each identifier is of the form schemaName.tableName. By default, the connector captures changes in every non-system table. Do not also set the |
||
An optional, comma-separated list of regular expressions that match fully-qualified table identifiers for tables whose changes you do not want the connector to capture. The connector captures changes in each non-system table that is not included in the exclude list. Each identifier is of the form schemaName.tableName. Do not also set the |
||
empty string |
An optional, comma-separated list of regular expressions that match the fully-qualified names of columns to exclude from change event values. Fully-qualified names for columns are of the form schemaName.tableName.columnName. Primary key columns are always included in the event’s key, even if they are excluded from the value. |
|
n/a |
An optional, comma-separated list of regular expressions that match the fully-qualified names of character-based columns whose values should be pseudonyms in change event values. A pseudonym is a field value that consists of the hashed value obtained by applying the |
|
|
Time, date, and timestamps can be represented with different kinds of precision: |
|
|
Controls whether a tombstone event should be generated after a delete event. |
|
|
Boolean value that specifies whether the connector should publish changes in the database schema to a Kafka topic with the same name as the database server ID. Each schema change is recorded with a key that contains the database name and a value that is a JSON structure that describes the schema update. This is independent of how the connector internally records database history. |
|
n/a |
An optional, comma-separated list of regular expressions that match the fully-qualified names of character-based columns. Fully-qualified names for columns are of the form schemaName.tableName.columnName. In change event records, values in these columns are truncated if they are longer than the number of characters specified by length in the property name. You can specify multiple properties with different lengths in a single configuration. Length must be a positive integer, for example, |
|
n/a |
An optional, comma-separated list of regular expressions that match the fully-qualified names of character-based columns. Fully-qualified names for columns are of the form schemaName.tableName.columnName. In change event values, the values in the specified table columns are replaced with length number of asterisk ( |
|
n/a |
An optional, comma-separated list of regular expressions that match the fully-qualified names of columns. Fully-qualified names for columns are of the form databaseName.tableName.columnName, or databaseName.schemaName.tableName.columnName. |
|
n/a |
An optional, comma-separated list of regular expressions that match the database-specific data type name for some columns. Fully-qualified data type names are of the form databaseName.tableName.typeName, or databaseName.schemaName.tableName.typeName. |
|
empty string |
A semicolon separated list of tables with regular expressions that match table column names. The connector maps values in matching columns to key fields in change event records that it sends to Kafka topics. This is useful when a table does not have a primary key, or when you want to order change event records in a Kafka topic according to a field that is not a primary key. |
The following advanced configuration properties have defaults that work in most situations and therefore rarely need to be specified in the connector’s configuration.
| Property | Default | Description |
|---|---|---|
|
Specifies the criteria for performing a snapshot when the connector starts: |
|
|
During a snapshot, controls the transaction isolation level and how long the connector locks the tables that are in capture mode. The possible values are: |
|
|
Specifies how the connector handles exceptions during processing of events. The possible values are: |
|
|
Positive integer value that specifies the number of milliseconds the connector should wait for new change events to appear before it starts processing a batch of events. Defaults to 1000 milliseconds, or 1 second. |
|
|
Positive integer value for the maximum size of the blocking queue. The connector places change events that it reads from the database log into the blocking queue before writing them to Kafka. This queue can provide backpressure for reading change-data tables when, for example, writing records to Kafka is slower than it should be or Kafka is not available. Events that appear in the queue are not included in the offsets that are periodically recorded by the connector. The |
|
|
Positive integer value that specifies the maximum size of each batch of events that the connector processes. |
|
|
Controls how frequently the connector sends heartbeat messages to a Kafka topic. The default behavior is that the connector does not send heartbeat messages. |
|
|
Specifies the prefix for the name of the topic to which the connector sends heartbeat messages. The format for this topic name is |
|
An interval in milliseconds that the connector should wait before performing a snapshot when the connector starts. If you are starting multiple connectors in a cluster, this property is useful for avoiding snapshot interruptions, which might cause re-balancing of connectors. |
||
|
During a snapshot, the connector reads table content in batches of rows. This property specifies the maximum number of rows in a batch. |
|
|
Positive integer value that specifies the maximum amount of time (in milliseconds) to wait to obtain table locks when performing a snapshot. If the connector cannot acquire table locks in this interval, the snapshot fails. How the connector performs snapshots provides details. Other possible settings are: |
|
Controls which table rows are included in snapshots. This property affects snapshots only. It does not affect events that the connector reads from the log. Specify a comma-separated list of fully-qualified table names in the form schemaName.tableName. |
||
|
Indicates whether field names are sanitized to adhere to Avro naming requirements. |
|
|
Determines whether the connector generates events with transaction boundaries and enriches change event envelopes with transaction metadata. Specify |
The connector also supports pass-through configuration properties that it uses when it creates Kafka producers and consumers:
-
All connector configuration properties that begin with the
database.history.producer.
prefix are used (without the prefix) when creating the Kafka producer that writes to the database history topic. -
All connector configuration properties that begin with the
database.history.consumer.
prefix are used (without the prefix) when creating the Kafka consumer that reads the database history when the connector starts.
For example, the following connector configuration properties secure connections to the Kafka broker:
database.history.producer.security.protocol=SSL
database.history.producer.ssl.keystore.location=/var/private/ssl/kafka.server.keystore.jks
database.history.producer.ssl.keystore.password=test1234
database.history.producer.ssl.truststore.location=/var/private/ssl/kafka.server.truststore.jks
database.history.producer.ssl.truststore.password=test1234
database.history.producer.ssl.key.password=test1234
database.history.consumer.security.protocol=SSL
database.history.consumer.ssl.keystore.location=/var/private/ssl/kafka.server.keystore.jks
database.history.consumer.ssl.keystore.password=test1234
database.history.consumer.ssl.truststore.location=/var/private/ssl/kafka.server.truststore.jks
database.history.consumer.ssl.truststore.password=test1234
database.history.consumer.ssl.key.password=test1234
Be sure to consult the Kafka documentation for all of the configuration properties for Kafka producers and consumers. Note that the Db2 connector uses the new consumer.
Also, the connector passes configuration properties that start with database.
to the JDBC URL, for example, database.applicationName=debezium
.
Monitoring
The Debezium Db2 connector provides three types of metrics that are in addition to the built-in support for JMX metrics that Zookeeper, Kafka, and Kafka Connect provide.
-
Snapshot metrics provide information about connector operation while performing a snapshot.
-
Streaming metrics provide information about connector operation when the connector is capturing changes and streaming change event records.
-
Schema history metrics provide information about the status of the connector’s schema history.
Debezium monitoring documentation provides details for how to expose these metrics by using JMX.
Snapshot metrics
The MBean is debezium.db2:type=connector-metrics,context=snapshot,server=<database.server.name>
.
| Attributes | Type | Description |
|---|---|---|
|
The last snapshot event that the connector has read. |
|
|
The number of milliseconds since the connector has read and processed the most recent event. |
|
|
The total number of events that this connector has seen since last started or reset. |
|
|
The number of events that have been filtered by include/exclude list filtering rules configured on the connector. |
|
|
The list of tables that are monitored by the connector. |
|
|
The length the queue used to pass events between the snapshotter and the main Kafka Connect loop. |
|
|
The free capacity of the queue used to pass events between the snapshotter and the main Kafka Connect loop. |
|
|
The total number of tables that are being included in the snapshot. |
|
|
The number of tables that the snapshot has yet to copy. |
|
|
Whether the snapshot was started. |
|
|
Whether the snapshot was aborted. |
|
|
Whether the snapshot completed. |
|
|
The total number of seconds that the snapshot has taken so far, even if not complete. |
|
|
Map containing the number of rows scanned for each table in the snapshot. Tables are incrementally added to the Map during processing. Updates every 10,000 rows scanned and upon completing a table. |
Streaming metrics
The MBean is debezium.db2:type=connector-metrics,context=streaming,server=<database.server.name>
.
| Attributes | Type | Description |
|---|---|---|
|
The last streaming event that the connector has read. |
|
|
The number of milliseconds since the connector has read and processed the most recent event. |
|
|
The total number of events that this connector has seen since last started or reset. |
|
|
The number of events that have been filtered by include/exclude list filtering rules configured on the connector. |
|
|
The list of tables that are monitored by the connector. |
|
|
The length the queue used to pass events between the streamer and the main Kafka Connect loop. |
|
|
The free capacity of the queue used to pass events between the streamer and the main Kafka Connect loop. |
|
|
Flag that denotes whether the connector is currently connected to the database server. |
|
|
The number of milliseconds between the last change event’s timestamp and the connector processing it. The values will incoporate any differences between the clocks on the machines where the database server and the connector are running. |
|
|
The number of processed transactions that were committed. |
|
|
The coordinates of the last received event. |
|
|
Transaction identifier of the last processed transaction. |
Schema history metrics
The MBean is debezium.db2:type=connector-metrics,context=schema-history,server=<database.server.name>
.
| Attributes | Type | Description |
|---|---|---|
|
One of |
|
|
The time in epoch seconds at what recovery has started. |
|
|
The number of changes that were read during recovery phase. |
|
|
the total number of schema changes applied during recovery and runtime. |
|
|
The number of milliseconds that elapsed since the last change was recovered from the history store. |
|
|
The number of milliseconds that elapsed since the last change was applied. |
|
|
The string representation of the last change recovered from the history store. |
|
|
The string representation of the last applied change. |
Management
After you deploy a Debezium Db2 connector, use the Debezium management UDFs to control Db2 replication (ASN) with SQL commands. Some of the UDFs expect a return value in which case you use the SQL VALUE
statement to invoke them. For other UDFs, use the SQL CALL
statement.
| Task | Command and notes |
|---|---|
|
|
|
|
|
|
|
|
|
|
|
Schema evolution
While a Debezium Db2 connector can capture schema changes, to update a schema, you must collaborate with a database administrator to ensure that the connector continues to produce change events. This is required by the way that Db2 implements replication.
For each table in capture mode, Db2’s replication feature creates a change-data table that contains all changes to that source table. However, change-data table schemas are static. If you update the schema for a table in capture mode then you must also update the schema of its corresponding change-data table. A Debezium Db2 connector cannot do this. A database administrator with elevated privileges must update schemas for tables that are in capture mode.
|
It is vital to execute a schema update procedure completely before there is a new schema update on the same table. Consequently, the recommendation is to execute all DDLs in a single batch so the schema update procedure is done only once. |
There are generally two procedures for updating table schemas:
Each approach has advantages and disadvantages.
 While this is the safer schema update procedure, it might not be feasible for applications with high-availability requirements.
-
One or more tables that are in capture mode require schema updates.
-
Suspend the application that updates the database.
-
Wait for the Debezium connector to stream all unstreamed change event records.
-
Stop the Debezium connector.
-
Apply all changes to the source table schema.
-
In the ASN register table, mark the tables with updated schemas as
INACTIVE
. -
xref:connectors/db2.adoc#debezium-db2-reinitialize-asn-service[Reinitialize the ASN capture service.
-
Remove the source table with the old schema from capture mode by running the Debezium UDF for removing tables from capture mode.
-
Add the source table with the new schema to capture mode by running the Debezium UDF for adding tables to capture mode.
-
In the ASN register table, mark the updated source tables as
ACTIVE
. -
Resume the application that updates the database.
-
Restart the Debezium connector.
Online schema update
An online schema update does not require application and data processing downtime.  Also, an online schema update procedure is simpler than the procedure for an offline schema update.
However, when a table is in capture mode, after a change to a column name, the Db2 replication feature continues to use the old column name. The new column name does not appear in Debezium change events. You must restart the connector to see the new column name in change events.
-
One or more tables that are in capture mode require schema updates.
-
Lock the source tables whose schema you want to change.
-
In the ASN register table, mark the locked tables as
INACTIVE
. -
Apply all changes to the schemas for the source tables.
-
Apply all changes to the schemas for the corresponding change-data tables.
-
In the ASN register table, mark the source tables as
ACTIVE
. -
Optional. Restart the connector to see updated column names in change events.
-
Lock the source table(s) to be changed.
-
In the ASN register table, mark the locked tables as
INACTIVE
. -
For each source table to be changed:
-
Export the data in the source table.
-
Truncate the source table.
-
Alter the source table and add the column.
-
Load the exported data into the altered source table.
-
Export the data in the source table’s corresponding change-data table.
-
Truncate the change-data table.
-
Alter the change-data table and add the column.
-
Load the exported data into the altered change-data table.
-
-
In the ASN register table, mark the tables as
INACTIVE
. This marks the old change-data tables as inactive, which allows the data in them to remain but they are no longer updated. -
Optional. Restart the connector to see updated column names in change events.


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title = "Profile Settings" url = "user/profile/edit" layout = "default" is_hidden = 0 [account] paramCode = "code" [session] security = "user" redirect = "/#promo-1" [imageUploader] == use Acme\Profile\Models\Profile; use RainLab\User\Controllers\Users; public $username; public $bio; public $nationality; public $favourite_team; public $position; public $fan_type; function onInit() { $this->imageUploader->bindModel('avatar', $this->account->user()); } public function user() { if (!Auth::check()) { return null; } return Auth::getUser()->profile; } public function onChange() { $username = Request::input('username'); $bio = Request::input('bio'); $nationality = Request::input('nationality'); $favourite_team = Request::input('favourite_team'); $position = Request::input('position'); $fan_type = Request::input('fan_type'); if (!$user = $this->user()) { // If the user has no profile, a record is added. $user = Auth::getUser()->profile(); $user->create([ 'username' => $username, 'bio' => $bio, 'nationality' => $nationality, 'favourite_team' => $favourite_team, 'position' => $position, 'fan_type' => $fan_type ]); return Redirect::to('/user/profile/edit/'); } else { $user->username = $username; $user->fill(post()); $user->save(); return Redirect::to('/user/profile/edit/'); } } ==


| | |
- builtins.object
-
- Cards
class Cards(builtins.object) |
| |
Cards(account, maxCards)
Cards Collection. |
| |
Methods defined here:
- __init__(self, account, maxCards)
- Cards Collection Default Constuctor.
Args:
account (Account): Card account.
maxCards (int): Maximum number of cards.
- __str__(self)
- Cards output.
Returns:
String: Output Card string.
- createCards(self)
- Create two cards.
- createRandomCards(self)
- Create a random cards collection.
- randomSelectedCard(self, account)
- Selecting a Card.
Args:
account (Account): Client account.
Returns:
Card: The selected Card.
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
- account
- cards
| |


Table of contents
- Derivation of the basic equation
- Fundamentals
- How to calculate stresses due to applied loads?
- Dynamics and non-linear analysis
Derivation of basic equation
Fundamentals
Let us consider a 3D body of volume V. It has an external surface S, with points on the body that are defined by co-ordinates $x, y, z$
. A portion of he body $S_{u}$
is constrained as shown below. A distributed force per unit area $f_{s}$
acts on a portion of the boundary surface $S_{fs}$
.
Let’s assume that the body deforms under the action of this force. Then the deformation of any point in the body is given by the three components of it’s displacement as
$$\{{u}\} = \begin{bmatrix} u \\ v \\ w \end{bmatrix}$$
where, $u,v,w$
are displacements in the $x,y,z$
directions.
A distributed force per unit volume $f_{b}$
may act on the body. This is given by
$$\{{f^{b}}\} = \begin{bmatrix} f_{x}^b \\ f_{y}^b \\ f_{z}^b \end{bmatrix}$$
Examples of $f^b\rightarrow$
gravity loads.
The surface loads is given by it’s components as
$$\{{f^{s}}\} = \begin{bmatrix} f_{x}^s \\ f_{y}^s \\ f_{z}^s \end{bmatrix}$$
Examples of $f^s\rightarrow$
pressure loads, contact forces.
Point load $f$
acting at a point $i$
is given by
$$\{{f^{i}}\} = \begin{bmatrix} f_{x}^i \\ f_{y}^i \\ f_{z}^i \end{bmatrix}$$
The resulting stresses and strains are given by
$$\{{\sigma}\} = \begin{bmatrix} \sigma_{xx} \\ \sigma_{yy} \\ \sigma_{zz} \\ \tau_{xy} \\ \tau_{xz} \\ \tau_{yz} \end{bmatrix}$$
$$\{{\epsilon}\} = \begin{bmatrix} \epsilon_{xx} \\ \epsilon_{yy} \\ \epsilon_{zz} \\ \gamma_{xy} \\ \gamma_{xz} \\ \gamma_{yz} \end{bmatrix}$$
We can relate the strains to displacement using
$$\{{\epsilon}\} = \begin{bmatrix} \frac{\delta u}{\delta x} \\ \frac{\delta v}{\delta x} \\ \frac{\delta w}{\delta x}
\\ \frac{\delta v}{\delta x} + \frac{\delta u}{\delta y} \\ \frac{\delta v}{\delta x} + \frac{\delta u}{\delta z} \\ \frac{\delta w}{\delta y} + \frac{\delta v}{\delta z} \end{bmatrix}$$
Let’s keep the material simply. Let us assume the material is linear elastic. Then, we can related the stress to strain as
$$\sigma=\begin{bmatrix} D \end{bmatrix} \begin{bmatrix} \epsilon \end{bmatrix}$$
How to calculate stresses due to applied loads
If you carefully look at equations above, you shall notice that if we can somehow calculate the displacements $u,v,w$
then we can compute the strains. If we know the strains, then we can compute the resulting stresses using the material behavior defined by $D$
.
So long story short, to get to the stresses, we need to compute the displacements due to the applied loads.
There are many different methods to get to the displacements. We will use the principle of Minimum Potential Energy here. It states that, as long as the system is stable, the total potential energy $\Pi$
of that system is zero.
$$\frac{\delta \Pi}{\delta U}= 0$$
The total potential energy of a system is given by the sum of the strain energy and the sum of work done by external forces. Thus, $\Pi = $
strain energy + external work
For a linear elastic body, the strain energy per unit volume is given by
$$\pi_{s} = \frac{1}{2}\{\sigma\}^T \{\epsilon\}$$
Thus total strain energy for the volume is
$$\Pi_{s} = \frac{1}{2}\int_{V} \{\sigma\}^T \{\epsilon\} dV$$
The total external work is the work done by all external forces as
$$\Pi_w = - \int_{V} \{u\}^T \{f^b\} dV - \int_{S} \{u\}^T \{f^s\} dS - \Sigma_{i}\{U_{i}\}^T \{{f^i\} }$$
Collecting everything, we can the expression for the total potential energy as,
$$\Pi= \frac{1}{2}\{\sigma\}^T \{\epsilon\} dV - \int_{V} \{u\}^T \{f^b\} dV - \int_{S} \{u\}^T \{f^s\} dS - \Sigma_{i}\{U_{i}\}^T \{{f^i\} }$$
In finite element analysis we divide the problem into a discrete parts that are represented by a number of finite elements. These elements are interconnected at nodes on the element boundaries. In the finite element approach the displacements measured within each element are assumed to be a function of the displacements of the nodes. Thus, the displacement within the element is related to the displacement of the nodes via an interpolation function known as a shape function. Thus the displacement can be further represented as
$$\{ u \}_{e} = \begin{bmatrix} S \end{bmatrix}_{e} \{U\}_{nodal} $$
where, $\begin{bmatrix} S \end{bmatrix}_{elem}$
is the shape function matrix for the element, $\{U\}_{nodal}$
is the nodal point displacement vector of the element. For clarity, the displacement within an element for an element with two nodes and four nodes is shown below.
For an element with two nodes $i$
and $j$
(Eg. Spring element)
$$\{ u \}_{e} = \begin{bmatrix} S_{i} & S_{j} \end{bmatrix} \begin{Bmatrix} U_{i} \\ U_{j} \end{Bmatrix} $$
For an element with 4 nodes $i,j, k, l$
$$\{ u \}_{e} = \begin{bmatrix} S_{i} & S_{j} & S_{k} & S_{l} \end{bmatrix} \begin{Bmatrix} U_{i} \\ U_{j} \\ U_{k} \\ U_{l} \end{Bmatrix} $$


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Was subjected to racial abuse: Jofra Archer
by ReutersHighlights
- Archer combined in a stubborn 59-run partnership for the ninth wicket with Sam Curran to delay the hosts' victory.
- Archer was born in Barbados and represented West Indies at Under-19 level.
- Archer was fast-tracked into the England side and made an impressive Test debut during the Ashes series against Australia.
WELLINGTON: England fast bowler Jofra Archer said on Monday he was subjected to "racial insults" by a spectator while batting during the final day of the opening Test against New Zealand at Bay Oval.
New Zealand cruised to an innings and 65-run win over England on the final day to take a 1-0 lead in the two-match series.
Archer scored 30 and combined in a stubborn 59-run partnership for the ninth wicket with Sam Curran to delay the hosts' victory.
"A bit disturbing hearing racial insults today whilst battling to help save my team, the crowd was been amazing this week except for that one guy," the 24-year-old said on Twitter.
Archer, who was born in Barbados and represented West Indies at Under-19 level, has been fast-tracked into the England side and made an impressive Test debut during the Ashes series against Australia.
According to protocol, International Cricket Council-appointed match referee Javagal Srinath of India is expected to mention the incident in his match report to the world governing body.
New Zealand Cricket said the security providers at the venue were unable to locate the perpetrator and the board will apologise to Archer.
"NZC will be examining CCTV footage and making further inquiries tomorrow in an endeavour to identify the man responsible," it said in a statement.
"NZC has zero tolerance towards abusive or offensive language at any of its venues and will refer any developments in the case to police.
"It will contact Mr Archer tomorrow to apologise for the unacceptable experience, and to promise increased vigilance in the matter when the teams next meet in Hamilton."
The second Test starts in Hamilton from Friday.


--- layout: post title: "Week in Review" date: 2017-12-17 09:00:00 +0000 tags: image: https://s3.amazonaws.com/audreywatters/2017-12-17-snow.jpg imagecredits: https://www.flickr.com/photos/thomashawk/2258137536 ---
Icon credits: The Noun Project


Priest Kanis:
I entreat you...
You will only be able to reach the location where the Shamaness is being held captive after defeating the evil creature named Balor.
You can enter the Water Dragon's Cave using the Contaminated Crystal from the Dark Cloud Mansion. Please be careful...and good luck!


Pre-reqs
- A Web Server
- PHP 5.3
- Redis 2.4 running locally on the defualt port
Info
This leaderboard supports the required features. I decided to use calendar days rather than time differences, as those tend to resonate better with players. For instance, the list of most improved this week is for the calendar week starting on the previous Sunday.
- Stores player metadata
- Stores score data
- Fast querying of top 10 all time scores
- Fast querying of most improved this week
- Fast querying of total player count
- Fast querying of players that have played today
- A utility to generate N new players, and 0-10 scores for each player (to get the requested 1MM scores you should add 200,000 players)
Add a Score
Generate Random Players/Scores
Note: This will take a bit (about 5 minutes for 200k on my Mac Book Pro 13"), since it is single threaded and re-sorts the leaderboard on every insert. This is obviously stupidly inefficient – O(log(n))*n – but I don't have time to speed it up. The approach I would take is to push everything into a temporary list, then do a sort once on that list using the Redis "SORT by STORE" command.
Empty DB
Top 10
| Rank | Player | Score | '.$score['rank'].' | '.$score['uid'].' | '.$score['score'].' | '; echo "\n"; } ?>
|---|
Top 10 Improved This Week
| Rank | Player | Score | '.$score['rank'].' | '.$score['uid'].' | '.$score['score'].' | '; echo "\n"; } ?>
|---|


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Knowing is not enough, we must apply. Willing is not enough, we must do. -Bruce Lee
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Main crops in Nagpur sugar cane,wheat,bajra,moong
Introduction
The greengram is a leguminous species, or pulse crop, grown mainly for its protein rich edible seeds. The greengram, also called mung, moong and mungbean in India and mungo in the Philippines, is prized among the pulse species, for its seeds are high in protein and easily digested when consumed as food. In symbiotic relationship with specific soil rhizobia of the genus Bradirhizobium, root nodules develop on moongbean in which atmospheric nitrogen is converted to forms available to the plant.
Soil and climate
Generally deep, well drained loam or sandy loam soils are very much suitable for cultivation of mungbean. It is a short day, warm season crop, grown mainly in semiarid to subhumid tropics with 600 to 1000 mm annual rainfall, 20 to 30 degreeÂ C mean temperature during the period of crop production and elevations not exceeding 1800 to 2000 m.
Planting season: The main planting season of greengram is considered to be first week of June- first week of July, at the onset of the South West monsoon.
Harvesting
The pods should be separated from the plant and threshed to separate the seeds. Or, entire plant may be cut at the ground level and threshed and cleaned.
Sugarcane, or sugar cane, are several species of tall perennial true grasses of the genus Saccharum, tribe Andropogoneae, native to the warm temperate to tropical regions of South Asia and Melanesia, and used for sugar production. Sugarcane, Saccharum officinarum L., an old energy source for human beings and, more recently, a replacement of fossil fuel for motor vehicles, was first grown in South East Asia and Western India. Around 327 B.C. it was an important crop in the Indian sub-continent. It was introduced to Egypt around 647 A.D. and, about one century later, to Spain (755 A.D.). Since then, the cultivation of sugarcane was extended to nearly all tropical and sub-tropical regions. Portuguese and Spaniards took it to the New World early in the XVI century. It was introduced to the United States of America (Louisiana) around 1741.
Climate and Soil-
Climate- • A long, warm growing season with a high incidence of solar radiation and adequate moisture (rainfall) - the plant uses from 148 to 300g of water to produce 1.0g of dry substance. • A fairly dry, sunny and cool, but frost free season for ripening and harvesting - moisture percentage drops steadily throughout the life of the sugarcane plant, from 83% in very young cane to 71% in mature cane, meanwhile sucrose grows from less than 10 to more than 45% of the dry weight. • Freedom from typhoons and hurricanes
Soil- Soil is a medium for plant growth. It provides nutrients, water and anchorage to the growing plants. Maintenance of proper physical, chemical and biological conditions of the soil is necessary for realizing higher growth, yield and quality of sugarcane. Sugarcane does not require any specific type of soil as it can be successfully raised on diverse soil types ranging from sandy soils to clay loams & heavy clays. A well drained, deep, loamy soil with a bulk density of 1.1 to 1.2 g/cm3 (1.3-1.4 g/cm3 in sandy soils) and total porosity, with an adequate balance between pores of various sizes, is higher than 50%; ground water table below 1.5 to 2.0 m from soil surface and an available water holding capacity of 15% or more (15 cm per meter depth of soil is considered ideal for sugarcane cultivation).
Watering Frequency-
Adequate available moisture throughout the growing period is important for obtaining maximum yields because vegetative growth including cane growth is directly proportional to the water transpired. Depending on climate, water requirements (ETm) of sugarcane are 1500 to 2500 mm evenly distributed over the growing season. The crop coefficient (kc) values, relating ETm to reference evapotranspiration (ETo) for the different growth stages are presented in the following table.
Harvesting-
Harvesting of sugarcane at a proper time i.e., peak maturity, by adopting right technique is necessary to realize maximum weight of the millable canes (thus sugar) produced with least possible field losses under the given growing environment • To harvest the cane at peak maturity (i.e., avoiding cutting of either over-matured or under-matured cane) • Cutting cane to ground level so that the bottom sugar rich internodes are harvested which add to yield and sugar • De-topping at appropriate height so that the top immature internodes are eliminated • Proper cleaning of the cane i.e., removing the extraneous matter such as leaves, trash, roots etc. • Quick disposal of the harvested cane to factory


{% extends "layouts/auth.html" %} {% block body_block %} {% load static %}
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It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. Many desktop publishing packages and web page editors now use Lorem Ipsum..
Read MoreThere are many variations of passages of Lorem Ipsum available, but the majority have suffered alteration in some form, by injected humour, or randomised words which don't look even slightly believable. If you are going to use a passage of Lorem Ipsum, you need to be sure there isn't anything embarrassing hidden in the middle of text..
Read MoreIt is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. Many desktop publishing packages and web page editors now use Lorem Ipsum..
Read MoreIt is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. Many desktop publishing packages and web page editors now use Lorem Ipsum..
Read MoreThere are many variations of passages of Lorem Ipsum available, but the majority have suffered alteration in some form, by injected humour, or randomised words which don't look even slightly believable. If you are going to use a passage of Lorem Ipsum, you need to be sure there isn't anything embarrassing hidden in the middle of text..
Read MoreIt is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. Many desktop publishing packages and web page editors now use Lorem Ipsum..
Read MoreIt is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. Many desktop publishing packages and web page editors now use Lorem Ipsum..
Read MoreIt is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. Many desktop publishing packages and web page editors now use Lorem Ipsum..
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Read MoreIt is a long established fact that a reader will be distracted..
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Algorithm 41
Task
Enter four numbers and print the
weighted average
.
The weights are: 1, 2, 3, 4.
Number 1:
Number 2:
Number 3:
Number 4:
Result


On this page you select the Tags which you want to assign to your selected ADT objects
You can also create new Global or new User Tags, directly on this page without creating them first in the Tags View
Limitation: Currently hierarchical tags can only be created in the Tags View


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DROWN is a serious vulnerability that affects HTTPS and other services that rely on SSL and TLS, some of the essential cryptographic protocols for Internet security. These protocols allow everyone on the Internet to browse the web, use email, shop online, and send instant messages without third-parties being able to read the communication.
DROWN allows attackers to break the encryption and read or steal sensitive communications, including passwords, credit card numbers, trade secrets, or financial data. Our measurements indicate 33% of all HTTPS servers are vulnerable to the attack.
Any communication between users and the server. This typically includes, but is not limited to, usernames and passwords, credit card numbers, emails, instant messages, and sensitive documents. Under some common scenarios, an attacker can also impersonate a secure website and intercept or change the content the user sees.
Websites, mail servers, and other TLS-dependent services are at risk for the DROWN attack, and many popular sites are affected. We used Internet-wide scanning to measure how many sites are vulnerable:
| Vulnerable at Disclosure (March 1) |
Still vulnerable (March 26) |
|
| HTTPS — Top one million domains | 25% | 15% |
| HTTPS — All browser-trusted sites | 22% | 16% |
| HTTPS — All sites | 33% | 28% |
Operators of vulnerable servers need to take action. There is nothing practical that browsers or end-users can do on their own to protect against this attack.
Modern servers and clients use the TLS encryption protocol. However, due to misconfigurations, many servers also still support SSLv2, a 1990s-era predecessor to TLS. This support did not matter in practice, since no up-to-date clients actually use SSLv2. Therefore, even though SSLv2 is known to be badly insecure, until now, merely supporting SSLv2 was not considered a security problem, because clients never used it.
DROWN shows that merely supporting SSLv2 is a threat to modern servers and clients. It allows an attacker to decrypt modern TLS connections between up-to-date clients and servers by sending probes to a server that supports SSLv2 and uses the same private key.
A server is vulnerable to DROWN if:
To protect against DROWN, server operators need to ensure that their private keys are not used anywhere with server software that allows SSLv2 connections. This includes web servers, SMTP servers, IMAP and POP servers, and any other software that supports SSL/TLS. You can use the form above to check whether your server appears to be exposed to the attack.
Disabling SSLv2 can be complicated and depends on the specific server software. We provide instructions here for several common products:
OpenSSL: OpenSSL is a cryptographic library used in many server products. For users of OpenSSL, the easiest and recommended solution is to upgrade to a recent OpenSSL version. OpenSSL 1.0.2 users should upgrade to 1.0.2g. OpenSSL 1.0.1 users should upgrade to 1.0.1s. Users of older OpenSSL versions should upgrade to either one of these versions. More details can be found in this OpenSSL blog post.
(Updated March 13th, 16:00 UTC) Microsoft IIS (Windows Server): Support for SSLv2 on the server side is enabled by default only on the OS versions that correspond to IIS 7.0 and IIS 7.5, namely Windows Vista, Windows Server 2008, Windows 7 and Windows Server 2008R2. This support can be disabled in the appropriate SSLv2 subkey for 'Server', as outlined in KB245030. Even if users have not taken the steps to disable SSLv2, the export-grade and 56-bit ciphers that make DROWN feasible are not supported by default.
Network Security Services (NSS): NSS is a common cryptographic library built into many server products. NSS versions 3.13 (released back in 2012) and above should have SSLv2 disabled by default. (A small number of users may have enabled SSLv2 manually and will need to take steps to disable it.) Users of older versions should upgrade to a more recent version. We still recommend checking whether your private key is exposed elsewhere, using the form above.
Other affected software and operating systems:
Instructions and information for:
Apache,
Postfix,
Nginx,
Debian,
Red Hat
Browsers and other clients: There is nothing practical that web browsers or other client software can do to prevent DROWN. Only server operators are able to take action to protect against the attack.
DROWN: Breaking TLS
using SSLv2 [PDF]
Nimrod Aviram, Sebastian Schinzel,
Juraj Somorovsky, Nadia Heninger, Maik Dankel,
Jens Steube, Luke Valenta, David Adrian,
J. Alex Halderman, Viktor Dukhovni,
Emilia Käsper, Shaanan Cohney,
Susanne Engels, Christof Paar, and
Yuval Shavitt
25th USENIX Security Symposium, Austin, TX, August 2016
More: Conference paper | Bibtex | Original tech report
The team can be contacted at<EMAIL_ADDRESS>DROWN stands for Decrypting RSA with Obsolete and Weakened eNcryption.
For the complete details, see our full technical paper. We also provide a brief technical summary below:
In technical terms, DROWN is a new form of cross-protocol Bleichenbacher padding oracle attack. It allows an attacker to decrypt intercepted TLS connections by making specially crafted connections to an SSLv2 server that uses the same private key.
The attacker begins by observing roughly several hundred connections between the victim client and server. The attacker will eventually be able to decrypt one of them. Collecting this many connections might involve intercepting traffic for a long time or tricking the user into visiting a website that quickly makes many connections to another site in the background. The connections can use any version of the SSL/TLS protocol, including TLS 1.2, so long as they employ the commonly used RSA key exchange method. In an RSA key exchange, the client picks a random session key and sends it to the server, encrypted using RSA and the server’s public key.
Next, the attacker repeatedly connects to the SSLv2 server and sends specially crafted handshake messages with modifications to the RSA ciphertext from the victim’s connections. (This is possible because unpadded RSA is malleable.) The way the server responds to each of these probes depends on whether the modified ciphertext decrypts to a plaintext message with the right form. Since the attacker doesn’t know the server’s private key, he doesn’t know exactly what the plaintext will be, but the way that the server responds ends up leaking information to the attacker about the secret keys used for the victim’s TLS connections.
The way this information is leaked can take two forms:
In the most general variant of DROWN, the attack exploits a fundamental weakness in the SSLv2 protocol that relates to export-grade cryptography that was introduced to comply with 1990s-era U.S. government restrictions. The attacker’s probes use a cipher that involves only 40 bits of RSA encrypted secret key material. The attacker can tell whether his modified ciphertext was validly formed by comparing the server’s response to all 240 possibilities—a moderately large computation, but one that we show can be inexpensively performed with GPUs. Overall, roughly 40,000 probe connections and 250 computation is needed to decrypt one out of 900 TLS connections from the victim. Running the computations for the full attack on Amazon EC2 costs about $440.
A majority of servers vulnerable to DROWN are also affected by an OpenSSL bug that results in a significantly cheaper version of the attack. In this special case, the attacker can craft his probe messages so that he immediately learns whether they had the right form without any large computation. In this case, the attacker needs about 17,000 probe connections in total to obtain the key for one out of 260 TLS connections from the victim, and the computation takes under a minute on a fast PC.
This special case stems from the complexity introduced by export-grade cryptography. The OpenSSL bug allows the attacker to mix export-grade and non-export-grade crypto parameters in order to exploit unexpected paths in the code.
This form of the attack is fast enough to allow an online man-in-the-middle (MitM) style of attack, where the attacker can impersonate a vulnerable server to the victim client. Among other advantages, such an attacker can force the client and server to use RSA key exchange (and can then decrypt the connection) even if they would normally prefer a different cipher. This lets the attacker target and break connections between modern browsers and servers that prefer perfect-forward-secret key exchange methods, such as DHE and ECDH.
We were able to execute this form of the attack in under a minute on a single PC.
DROWN was developed by researchers at Tel Aviv University, Münster University of Applied Sciences, Ruhr University Bochum, the University of Pennsylvania, the Hashcat project, the University of Michigan, Two Sigma, Google, and the OpenSSL project: Nimrod Aviram, Sebastian Schinzel, Juraj Somorovsky, Nadia Heninger, Maik Dankel, Jens Steube, Luke Valenta, David Adrian, J. Alex Halderman, Viktor Dukhovni, Emilia Käsper, Shaanan Cohney, Susanne Engels, Christof Paar, and Yuval Shavitt
The team can be contacted at<EMAIL_ADDRESS>Yes. The DROWN attack itself was assigned CVE-2016-0800.
DROWN is made worse by two additional OpenSSL implementation vulnerabilities. CVE-2015-3197, which affected OpenSSL versions prior to 1.0.2f and 1.0.1r, allows a DROWN attacker to connect to the server with disabled SSLv2 ciphersuites, provided that support for SSLv2 itself is enabled. CVE-2016-0703, which affected OpenSSL versions prior to 1.0.2a, 1.0.1m, 1.0.0r, and 0.9.8zf, greatly reduces the time and cost of carrying out the DROWN attack.
Yes. We’ve been able to execute the attack against OpenSSL versions that are vulnerable to CVE-2016-0703 in under a minute using a single PC. Even for servers that don’t have these particular bugs, the general variant of the attack, which works against any SSLv2 server, can be conducted in under 8 hours at a total cost of $440.
We have no reason to believe that DROWN has been exploited in the wild prior to this disclosure. Since the details of the vulnerability are now public, attackers may start exploiting it at any time, and we recommend taking the countermeasures explained above as soon as possible.
Indeed, SSLv2 has long known to be weak when clients and servers use it to communicate, and so nearly every modern client uses a more recent protocol. DROWN shows that merely allowing SSLv2, even if no legitimate clients ever use it, is a threat to modern servers and clients. It allows an attacker to decrypt modern TLS connections between up-to-date clients and servers by sending probes to any server that supports SSLv2 using the same private key.
No. DROWN allows an attacker to decrypt one connection at a time. The attacker does not learn the server’s private key.
Yes. Some variants of the attack can be used to perform MitM attacks against TLS or QUIC. More details can be found in sections 5.3 and 7 of the technical paper.
Surprisingly, no. The active MitM form of the attack allows an attacker to target servers and clients that prefer non-RSA key exchange methods. See sections 5.3 and 7 of the technical paper.
Probably not. As the attacker does not learn the server’s private key, there’s no need to obtain new certificates. The only action required is disabling SSLv2 as per the countermeasures explained above. If you cannot confidently determine that SSLv2 is disabled on every device or server that uses your server’s private key, you should generate a fresh key for the server and obtain a new certificate.
No. There is nothing practical that web browsers or other client software can do to prevent DROWN. Only server operators are able to take action to protect against the attack.
Yes, that’s a reasonable precaution, although it will also prevent our scanners from being able to help you identify vulnerable servers. You might consider first running the test suite to identify vulnerable servers and only then filtering SSLv2 traffic. You should also use the countermeasures explained above.
Possibly. If you run a server and can be certain no one made a large number of SSLv2 connections to any of your servers (for example, by examining IDS or server logs), then you weren’t attacked. Your logs may contain a small number of SSLv2 connections from the Internet-wide scans that we conducted over the past few months to measure the prevalence of the vulnerability.
Yes. Even if you’re certain that you have SSLv2 disabled on your HTTPS server, you may be reusing your private key on another server (such as an email server) that does support SSLv2. We recommend manually inspecting all servers that use your private key. In addition, you can check whether your private key is exposed elsewhere on the Internet using the form above.
Security against DROWN is not possible for that embedded device. If you must keep that device running, make sure it uses a different RSA private key than any other servers and devices. You can also limit the scope of attack by using a firewall to filter SSLv2 traffic from outside your organization. In all circumstances, maintaining support for SSLv2 should be a last resort.
Unfortunately, no. Although SSLLabs provides an invaluable suite of security tests, right now it only checks whether your HTTPS server directly allows SSLv2. You’re just as much at risk if your site’s certificate or key is used anywhere else on a server that does support SSLv2. Common examples include SMTP, IMAP, and POP mail servers, and secondary HTTPS servers used for specific web applications. SSLLabs doesn’t yet check for this kind of cross-server exposure to DROWN, but our DROWN check tool attempts to.
You can also download and run our scanner utility. This utility only detects SSLv2 support on a single port. It cannot detect the common scenario, explained above, where a web server that doesn't support SSLv2 is vulnerable because it shares its public key with an email server that does. We strongly recommend using the online scanner above, when at all possible.
Due to CVE-2015-3197, OpenSSL may still accept SSLv2 connections even if all SSLv2 ciphers are disabled.
Not in the immediate future. There are still too many servers vulnerable to the attack.
For the third time in a year, a major Internet security vulnerability has resulted from the way cryptography was weakened by U.S. government policies that restricted exporting strong cryptography until the late 1990s. Although these restrictions, evidently designed to make it easier for NSA to decrypt the communication of people abroad, were relaxed nearly 20 years ago, the weakened cryptography remains in the protocol specifications and continues to be supported by many servers today, adding complexity—and the potential for catastrophic failure—to some of the Internet’s most important security features.
The U.S. government deliberately weakened three kinds of cryptographic primitives: RSA encryption, Diffie-Hellman key exchange, and symmetric ciphers. FREAK exploited export-grade RSA, and Logjam exploited export-grade Diffie-Hellman. Now, DROWN exploits export-grade symmetric ciphers, demonstrating that all three kinds of deliberately weakened crypto have come to put the security of the Internet at risk decades later.
Today, some policy makers are calling for new restrictions on the design of cryptography in order to prevent law enforcement from “going dark.” While we believe that advocates of such backdoors are acting out of a good faith desire to protect their countries, history’s technical lesson is clear: weakening cryptography carries enormous risk to all of our security.


Cindy had so many things to do. She had to clean her room, wash the dishes, and practice her dance steps. She did not know how to do so many things at once! Cindy sat at her desk to make a plan. She wrote all the things she needed to do on a huge sheet of paper. She made three columns. In the first column, she wrote "Clean room." In the second, she wrote "Wash dishes." In the third column, she wrote "Practice dance." Next, she wrote a time below each task. By doing this, she identified a time slot so she could finish all her chores. Cindy made a great plan! She even had time at the end of the day to watch a film with her family!
in-context


Do you have the Arduino IDE installed?
go to the Arduino software download page to get the IDE
Install according to instructions
Open your device manager (Win+R + devmgmt.msc)
make sure the device is recognized and appears as a valid COM port in your device manager:
is this what you see? (COM port number might be different)
go to this site to get the driver.
download the correct installer according to your OS version
install the driver and make sure the device now appears as a valid COM port
Open the Arduino IDE and open the preferences menu (File->Preferences or Ctrl+,)
insert the following URL to the "Additional Boards Manager URLs":
http://arduino.esp8266.com/stable/package_esp8266com_index.json
Are you on Intel's office network (Not "Guest")?
On the preferences menu switch to "Network" tab
select "Manual proxy configuration"
Host name: proxy.iil.intel.com
Port Number: 911
Open the Boards Manager (Tools->Board->Boards Manager...)
Search for "ESP8266" and install the boards package
You should now select the board (NodeMCU 1.0)
and make sure the correct COM port is selected as well
now that everything is set up, let's try to connect to the AP
the AP name is "intel makers"
and the password is "1234567890"
you can use the code below as a reference
#include <ESP8266WiFi.h>
const char* ssid = "intel makers";
const char* password = "1234567890";
#define ONBOARD_LED_PIN D4
void setup() {
// setup the on-board pin (D4) to output mode
pinMode(ONBOARD_LED_PIN, OUTPUT);
// start serial connection
Serial.begin(115200);
Serial.println("");
Serial.print("Connecting to ");
Serial.println(ssid);
// set WiFi to STA mode and connect to AP
WiFi.mode(WIFI_STA);
WiFi.begin(ssid, password);
// wait until connection is complete
while (WiFi.status() != WL_CONNECTED) {
delay(500);
Serial.print(".");
}
Serial.println("");
Serial.println("WiFi connected");
Serial.println("IP address: ");
Serial.println(WiFi.localIP());
}
void loop()
{
// toggle the LED each second
digitalWrite(ONBOARD_LED_PIN, HIGH);
delay(1000);
digitalWrite(ONBOARD_LED_PIN, LOW);
delay(1000);
}
open the serial monitor (Ctrl+Shift+M)
you should see a similar message
if you don't - check for serial monitor rate (set to 115200)
if the dots don't stop - make sure the SSID and password are correct
Click "Test me" when you are ready.


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Figure 1
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Scatter plot of Pattern Correlation Coefficient (PCC) and no ... |
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Figure 2
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Spatial distribution of JJAS mean: ( a) Surface Air Temperat ... |
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Figure 3
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Spatial distribution of JJAS mean: ( a) Surface Air Temperat ... |
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Figure 4
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Scatter plot of PCC and Normalized RMSE for ( a) Monsoon, ( ... |
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Figure 5
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The scatter plot of PCC and Normalized RMSE is shown for fiv ... |
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Figure 6
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Spatial pattern of JJAS mean: ( a) Surface Air Temperature i ... |
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Figure 7
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( a) Scatter plot of PCC and Normalized RMSE for control, op ... |
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Figure 8
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Spatial pattern of JJAS mean: ( a) Surface Air Temperature f ... |


Formerly an environmental scientist, now pursuing a career in data science. His favorite language is Python. His goal is to work in the sports industry, analyzing tennis matches, but will settle for any job in Data Science at the moment. Hire him, please. If you found this bio funny, please email him at<EMAIL_ADDRESS>Formerly an environmental scientist, now pursuing a career in data science. His favorite language is Python. His goal is to work in the sports industry, analyzing tennis matches, but will settle for any job in Data Science at the moment. Hire him, please. If you found this bio funny, please email him at<EMAIL_ADDRESS>Formerly an environmental scientist, now pursuing a career in data science. His favorite language is Python. His goal is to work in the sports industry, analyzing tennis matches, but will settle for any job in Data Science at the moment. Hire him, please. If you found this bio funny, please email him at<EMAIL_ADDRESS>Formerly an environmental scientist, now pursuing a career in data science. His favorite language is Python. His goal is to work in the sports industry, analyzing tennis matches, but will settle for any job in Data Science at the moment. Hire him, please. If you found this bio funny, please email him at kylebeng@gmail.com


Hi. I am fine.
Thanks,
Alex
Date: Thu, 26 Jun 2014 13:53:45 +0400
Subject: Test message
From<EMAIL_ADDRESS>To<EMAIL_ADDRESS>Hello! How are you?
Thanks,
Sasha.


We know how large objects will act, but things on small scale.
Problems trying to resolve the conflict between the two major realms of Classical physics: Newtonian mechanics
Problems trying to resolve the conflict between
the two major realms of Classical physics: Newtonian mechanics
Problems trying to resolve the conflict between the two major realms of Classical physics: Newtonian mechanics
Slate helps you see how many more days you need to work to reach your financial goal.
Slate helps you see how many more days you need to work to reach your financial goal.
Slate helps you see how many more days you need to work to reach your financial goal.
Problems trying to resolve the conflict between the two major realms of Classical physics: Newtonian mechanics
the quick fox jumps over the lazy dog


TABLE OF INTERACTIONS WITH
ANTIPARASITICS THAT TEND TO INDUCE TORSADES DE POINTES
From the French ANSM drug interactions document of September 2016, p. 27
ANTIPARASITICS THAT TEND TO INDUCE TORSADES DE POINTES CLASS CODE: P01B-001 |
SUBSTANCES THAT TEND TO INDUCE TORSADES DE POINTES CLASS CODE: C01-N05 |
Increased risk of ventricular arrhythmias, especially of torsades de pointes |
Contraindication with citalopram, domperidone, escitalopram, hydroxyzine and piperaquine Not recommended with the other medications that tend to induce torsades de pointes If this is possible, interrupt one of the two treatments. If administering the substances together cannot be avoided, testing of the QT before treatment and EKG monitoring |