Is there a view to get statistics about the number of writes per day in an Oracle database, and the amount of data associated ?
I had a view over these : V$METRIC_HISTORY, V$METRIC, but I did not find something so relevant about that.
Thanks for your suggestions
I would recommend looking at DBA_HIST_FILESTATXS view :
DBA_HIST_FILESTATXS displays information about file read/write statistics. This view contains snapshots of V$FILESTAT.
Following columns should be of interest for you :
PHYWRTS : Number of times DBWR is required to write
PHYBLKWRT : Number of blocks written to disk, which may be the same as PHYWRTS if all writes are single blocks
Note :
if you want to know the volume written, you need to multiply PHYBLKWRT with BLOCK_SIZE
if you want to filter by dates, you have to JOIN with view dba_hist_snapshot, that stores the snapshot history
Related
I could need some help with a Anylogic Model.
Model (short): Manufacturing scenario with orders move in a individual route. The workplaces (WP) are dynamical created by simulation start. Their names, quantity and other parameters are stored in a database (excel Import). Also the orders are created according to an import. The Agent population "order" has a collection routing which contains the Workplaces it has to stop in the specific order.
Target: I want a moveTo block in main which finds the next destination of the agent order.
Problem and solution paths:
I set the destination Type to agent and in the Agent field I typed a function agent.getDestination(). This function is in order which returns the next entry of the collection WP destinationName = routing.get(i). With this I get a Datatype error (while run not compiling). I quess it's because the database does not save the entrys as WP Type but only String.
Is there a possiblity to create a collection with agents from an Excel?
After this I tried to use the same getDestination as String an so find via findFirst the WP matching the returned name and return it as WP. WP targetWP = findFirst(wps, w->w.name == destinationName);
Of corse wps (the population of Workplaces) couldn't be found.
How can I search the population?
Maybe with an Agentlink?
I think it is not that difficult but can't find an answer or a solution. As you can tell I'm a beginner... Hope the description is good an someone can help me or give me a hint :)
Thanks
Is there a possiblity to create a collection with agents from an Excel?
Not directly using the collection's properties and, as you've seen, you can't have database (DB) column types which are agent types.1
But this is relatively simple to do directly via Java code (and you can use the Insert Database Query wizard to construct the skeleton code for you).
After this I tried to use the same getDestination as String an so find via findFirst the WP matching the returned name and return it as WP
Yes, this is one approach. If your order details are in Excel/the database, they are presumably referring to workplaces via some String ID (which will be a parameter of the workplace agents you've created from a separate Excel worksheet/database table). You need to use the Java equals method to compare strings though, not == (which is for comparing numbers or whether two objects are the same object).
I want a moveTo block in main which finds the next destination of the agent order
So the general overall solution is
Create a population of Workplace agents (let's say called workplaces in Main) from the DB, each with a String parameter id or similar mapped from a DB column.
Create a population of Order agents (let's say called orders in Main) from the DB and then, in their on-startup action, set up their collection of workplace IDs (type ArrayList, element class String; let's say called workplaceIDsList) using data from another DB table.
Order probably also needs a working variable storing the next index in the list that it needs to go to (so let's say an int variable nextWorkplaceIndex which starts at 0).
Write a function in Main called getWorkplaceByID that has a single String argument id and returns a Workplace. This gets the workplace from the population that matches the ID; a one-line way similar to yours is findFirst(workplaces, w -> w.id.equals(id)).
The MoveTo block (which I presume is in Main) needs to move the Order to an agent defined by getWorkplaceByID(agent.workplaceIDsList.get(nextWorkplaceIndex++)). (The ++ bit increments the index after evaluating the expression so it is ready for the next workplace to go to.)
For populating the collection, you'd have two tables, something like the below (assuming using strings as IDs for workplaces and orders):
orders table: columns for parameters of your orders (including some String id column) other than the workplace-list. (Create one Order agent per row.)
order_workplaces table: columns order_id, sequence_num and workplace_id (so with multiple rows specifying the sequence of workplace IDs for an order ID).
In the On startup action of Order, set up the skeleton query code via the Insert Database Query wizard as below (where we want to loop through all rows for this order's ID and do something --- we'll change the skeleton code to add entries to the collection instead of just printing stuff via traceln like the skeleton code does).
Then we edit the skeleton code to look like the below. (Note we add an orderBy clause to the initial query so we ensure we get the rows in ascending sequence number order.)
List<Tuple> rows = selectFrom(order_workplaces)
.where(order_workplaces.order_id.eq(id))
.orderBy(order_workplaces.sequence_num.asc())
.list();
for (Tuple row : rows) {
workplaceIDsList.add(row.get(order_workplaces.workplace_id));
}
1 The AnyLogic database is a normal relational database --- HSQLDB in fact --- and databases only understand their own specific data types like VARCHAR, with AnyLogic and the libraries it uses translating these to Java types like String. In the user interface, AnyLogic makes it look like you set the column types as int, String, etc. but these are really the Java types that the columns' contents will ultimately be translated into.
AnyLogic does support columns which have option list types (and the special Code type column for columns containing executable Java code) but these are special cases using special logic under the covers to translate the column data (which is ultimately still a string of characters) into the appropriate option list instance or (for Code columns) into compiled-on-the-fly-and-then-executed Java).
Welcome to Stack Overflow :) To create a Population via Excel Import you have to create a method and call Code like this. You also need an empty Population.
int n = excelFile.getLastRowNum(YOUR_SHEET_NAME);
for(int i = FIRST_ROW; i <= n; i++){
String name = excelFile.getCellStringValue(YOUR_SHEET_NAME, i, 1);
double SEC_PARAMETER_TO_READ= excelFile.getCellNumericValue(YOUR_SHEET_NAME, i, 2);
WP workplace = add_wps(name, SEC_PARAMETER_TO_READ);
}
Now if you want to get a workplace by name, you have to create a method similar to your try.
Functionbody:
WP workplaceToFind = wps.findFirst(w -> w.name.equals(destinationName));
if(workplaceToFind != null){
//do what ever you want
}
We are using MarkLogic 9.0.8.2
We have setup MarkLogic cluster, ingested around 18M XML documents, few indexes have been created like Fields, PathRange & so on.
Now while setting up another environment with configuration, indexs, same number of records but i am not able to understand why the total size on database status page is different from previous environment.
So i started comparing database status page of both clusters where i can see size per forest/replica forest and all.
So in this case, i would like to know size for each
Database
Index
Also would like to know (instead of expanding each thru admin interface) the total indexes in given database
Option within Admin interface OR thru xQuery will also do.
MarkLogic does not break down the index sizes separately from the Database size. One reason for this is because the data is stored together with the Universal Index.
You could approximate the size of the other indexes by creating them one at a time, and checking the size before and after the reindexer runs, and the deleted fragments are merged out. We usually don't find a lot of benefit it trying to determine the exact index sizes, since the benefits they provide typically outweigh the cost of storage.
It's hard to say exactly why there is a size discrepancy. One common cause would be the number of deleted fragments in each database. Deleted fragments are pieces of data that have been marked for deletion (usually due to an update, delete or other change). Deleted fragments will continue to consume database space until they are merged out. This happens by default, or it can be manually started at the forest or database level.
The database size, and configured indexes can be determined through the Admin UI, Query Console (QConsole) or via the MarkLogic REST Management API (RMA) endpoints. QConsole supports a number of languages, but server side Javascript and XQuery are the most common. RMA can return results in XML or JSON.
Database Size:
REST: http://[host-name]:8002/manage/v2/databases/[database-name]?view=status
QConsole: Sum the disk size elements for the stands from xdmp.forestStatus(javascript) or xdmp:forest-status(XQuery) for all the forests in the database.
Configured Indexes:
REST: http://[host-name]:8002/manage/v2/databases/\database-name]?view=package
QConsole: Use xdmp.getConfiguration(javascript) or xdmp:get-configuration(XQuery) in conjunction with the xdmp.databaseGet[index type] or xdmp:database-get-[index type]
for $db-id in xdmp:databases()
let $db-name := xdmp:database-name($db-id)
let $db-size :=
fn:sum(
for $f-id in xdmp:database-forests($db-id)
let $f-status := xdmp:forest-status($f-id)
let $space := $f-status/forest:device-space
let $f-name := $f-status/forest:forest-name
let $f-size :=
fn:sum(
for $stand in $f-status/forest:stands/forest:stand
let $stand-size := $stand/forest:disk-size/fn:data(.)
return $space
)
return $f-size
)
order by $db-size descending
return $db-name || " = " || $db-size
I'm having a bit of a trouble with the continuous queries in influxdb 0.8.8.
I'm trying to create a continuous query but it seems that the where clauses are ignored. I'm aware about the restrictions mentioned here: http://influxdb.com/docs/v0.8/api/continuous_queries.html but I don't consider that this would be the case here.
One row in the time series would contain data like this:
{"hex":"06a0b6", "squawk":"3421", "flight":"QTR028 ", "lat":99.867630, "lon":66.447365, "validposition":1, "altitude":39000, "vert_rate":-64,"track":125, "validtrack":1,"speed":482, "messages":201, "seen":219}
The query I'm running and works is the following:
select * from flight_series where time > now() - 30m and flight !~ /^$/ and validtrack = 1 and validposition = 1;
Trough it I'm trying to take the last 30 minutes from the current time, check that the flight field is no whitespaces and that the track/position are valid.
The query returns successfully but when I'm adding the
into filtered_log
part the 'where' clause is ignored.
How can I create a continuous query which takes the above-mentioned conditions into consideration? At least, how could I extract with one continuous query only the rows which have the valid track/heading set to 1 and the flight is not whitespace/empty string? The time constraint I could eliminate from the query and translate into shard retention/duration.
Also, could I specify to in the continuous query to save the data into a time-series which is located into another database (which has a more relaxed retention/duration policy)?
Thank you!
Later edit:
I've managed to do something closer to my need by using the following cq:
"select time, sequence_number, altitude, vert_rate, messages, squawk, lon, lat, speed, hex, seen from current_flights where ((flight !~ /^$/) AND (validtrack = 1)) AND (validposition = 1) into flight.[flight]"
This creates a series for each 'flight' even for those which have a whitespace in the 'flight' field -- for which a flight. series is built.
How could I specify the retention/duration policies for the series generated by the cq above? Can I do something like:
"spaces": [
{
"name": "flight",
"retentionPolicy": "1h",
"shardDuration": "30m",
"regex": "/.*/",
"replicationFactor": 1,
"split": 1
},
...
which would give me a retention of 1h and shard duration of 30m?
I'm a bit confused about where those series are stored, which shard space?
Thanks!
P.S.: My final goal would be the following:
Have a 'window' of 15-30min max with all the flights around, process some data from them and after that period is over discard the data but in the same time move/copy it to another long-term db/series which can be used for historical purposes.
You cannot put time restrictions into the WHERE clause of a continuous query. The server will generate the time restrictions as needed when the CQ runs and must ignore all others. I suspect if you leave out the time restriction the rest of the WHERE clause will be fine.
I don't believe CQs in 0.8 require an aggregation in the SELECT, but you do need to have GROUP BY clause to tell the CQ how often to run. I'm not sure what you would GROUP BY, perhaps the flight?
You can specify a different retention policy when writing to the new series but not a new database. In 0.8 the retention policy for a series is determined by regex matching on the series name. As long as you select a series name correctly it will go into your desired retention policy.
EDIT: updates for new questions
How could I specify the retention/duration policies for the series
generated by the cq above?
In 0.8.x, the shard space to which a series belongs controls the retention policy. The regex on the shard space determines which series belong to that shard. The shard space regex is evaluated newest to oldest, meaning the first created shard space will be the last regex evaluated. Unfortunately, I do know if it is possible to create new shard spaces once the database exists. See this discussion on the mailing list for more: https://groups.google.com/d/msgid/influxdb/ce3fc641-fbf2-4b39-9ce7-77e65c67ea24%40googlegroups.com
Can I do something like:
"spaces": [
{
"name": "flight",
"retentionPolicy": "1h",
"shardDuration": "30m",
"regex": "/.*/",
"replicationFactor": 1,
"split": 1
}, ... which would give me a retention of 1h and shard duration of 30m?
That shard space would have a shard duration of 30 minutes, retaining data for 1 hour, meaning any series would only exist in three shards, the current hot shard, the current cold shard, and the shard waiting for deletion.
The regex is /./, meaning it would match any series, not just the 'flight.' series. Perhaps /flight../ is a better regex if you only want those series generated by the CQ in that shard space.
I read in "hadoop design pattern" book, "HBase supports batch queries, so it would be ideal to buffer all the queries we want to execute up to some predetermined size. This constant depends on how many records you can comfortably store in memory before querying HBase."
I tried to search some examples online but couldn't find any, can someone show me the example using java map reduce?
Thanks.
Dan
Is this what you want? You can save HBase Get object in a list and submit the list at the same time. It's a little better than invoke table.get(get) multiple times.
Configuration conf = HBaseConfiguration.create();
pool = new HTablePool(conf, 5);
HTableInterface table = pool.getTable('table');
List<Get> gets = new ArrayList<Get>();
table.get(gets);
I've been using SQL Server to store historical time series data for a couple hundred thousand objects, observed about 100 times per day. I'm finding that queries (give me all values for object XYZ between time t1 and time t2) are too slow (for my needs, slow is more then a second). I'm indexing by timestamp and object ID.
I've entertained the thought of using somethings a key-value store like MongoDB instead, but I'm not sure if this is an "appropriate" use of this sort of thing, and I couldn't find any mentions of using such a database for time series data. ideally, I'd be able to do the following queries:
retrieve all the data for object XYZ between time t1 and time t2
do the above, but return one date point per day (first, last, closed to time t...)
retrieve all data for all objects for a particular timestamp
the data should be ordered, and ideally it should be fast to write new data as well as update existing data.
it seems like my desire to query by object ID as well as by timestamp might necessitate having two copies of the database indexed in different ways to get optimal performance...anyone have any experience building a system like this, with a key-value store, or HDF5, or something else? or is this totally doable in SQL Server and I'm just not doing it right?
It sounds like MongoDB would be a very good fit. Updates and inserts are super fast, so you might want to create a document for every event, such as:
{
object: XYZ,
ts : new Date()
}
Then you can index the ts field and queries will also be fast. (By the way, you can create multiple indexes on a single database.)
How to do your three queries:
retrieve all the data for object XYZ
between time t1 and time t2
db.data.find({object : XYZ, ts : {$gt : t1, $lt : t2}})
do the above, but return one date
point per day (first, last, closed to
time t...)
// first
db.data.find({object : XYZ, ts : {$gt : new Date(/* start of day */)}}).sort({ts : 1}).limit(1)
// last
db.data.find({object : XYZ, ts : {$lt : new Date(/* end of day */)}}).sort({ts : -1}).limit(1)
For closest to some time, you'd probably need a custom JavaScript function, but it's doable.
retrieve all data for all objects for
a particular timestamp
db.data.find({ts : timestamp})
Feel free to ask on the user list if you have any questions, someone else might be able to think of an easier way of getting closest-to-a-time events.
This is why databases specific to time series data exist - relational databases simply aren't fast enough for large time series.
I've used Fame quite a lot at investment banks. It's very fast but I imagine very expensive. However if your application requires the speed it might be worth looking it.
There is an open source timeseries database under active development (.NET only for now) that I wrote. It can store massive amounts (terrabytes) of uniform data in a "binary flat file" fashion. All usage is stream-oriented (forward or reverse). We actively use it for the stock ticks storage and analysis at our company.
I am not sure this will be exactly what you need, but it will allow you to get the first two points - get values from t1 to t2 for any series (one series per file) or just take one data point.
https://code.google.com/p/timeseriesdb/
// Create a new file for MyStruct data.
// Use BinCompressedFile<,> for compressed storage of deltas
using (var file = new BinSeriesFile<UtcDateTime, MyStruct>("data.bts"))
{
file.UniqueIndexes = true; // enforces index uniqueness
file.InitializeNewFile(); // create file and write header
file.AppendData(data); // append data (stream of ArraySegment<>)
}
// Read needed data.
using (var file = (IEnumerableFeed<UtcDateTime, MyStrut>) BinaryFile.Open("data.bts", false))
{
// Enumerate one item at a time maxitum 10 items starting at 2011-1-1
// (can also get one segment at a time with StreamSegments)
foreach (var val in file.Stream(new UtcDateTime(2011,1,1), maxItemCount = 10)
Console.WriteLine(val);
}
I recently tried something similar in F#. I started with the 1 minute bar format for the symbol in question in a Space delimited file which has roughly 80,000 1 minute bar readings. The code to load and parse from disk was under 1ms. The code to calculate a 100 minute SMA for every period in the file was 530ms. I can pull any slice I want from the SMA sequence once calculated in under 1ms. I am just learning F# so there are probably ways to optimize. Note this was after multiple test runs so it was already in the windows Cache but even when loaded from disk it never adds more than 15ms to the load.
date,time,open,high,low,close,volume
01/03/2011,08:00:00,94.38,94.38,93.66,93.66,3800
To reduce the recalculation time I save the entire calculated indicator sequence to disk in a single file with \n delimiter and it generally takes less than 0.5ms to load and parse when in the windows file cache. Simple iteration across the full time series data to return the set of records inside a date range in a sub 3ms operation with a full year of 1 minute bars. I also keep the daily bars in a separate file which loads even faster because of the lower data volumes.
I use the .net4 System.Runtime.Caching layer to cache the serialized representation of the pre-calculated series and with a couple gig's of RAM dedicated to cache I get nearly a 100% cache hit rate so my access to any pre-computed indicator set for any symbol generally runs under 1ms.
Pulling any slice of data I want from the indicator is typically less than 1ms so advanced queries simply do not make sense. Using this strategy I could easily load 10 years of 1 minute bar in less than 20ms.
// Parse a \n delimited file into RAM then
// then split each line on space to into a
// array of tokens. Return the entire array
// as string[][]
let readSpaceDelimFile fname =
System.IO.File.ReadAllLines(fname)
|> Array.map (fun line -> line.Split [|' '|])
// Based on a two dimensional array
// pull out a single column for bar
// close and convert every value
// for every row to a float
// and return the array of floats.
let GetArrClose(tarr : string[][]) =
[| for aLine in tarr do
//printfn "aLine=%A" aLine
let closep = float(aLine.[5])
yield closep
|]
I use HDF5 as my time series repository. It has a number of effective and fast compression styles which can be mixed and matched. It can be used with a number of different programming languages.
I use boost::date_time for the timestamp field.
In the financial realm, I then create specific data structures for each of bars, ticks, trades, quotes, ...
I created a number of custom iterators and used standard template library features to be able to efficiently search for specific values or ranges of time-based records.