I wrote a spark program in scala, of which the main codes are:
val centers:Array[(Vector,Double)] = initCenters(k)
val sumsMap:Map(int,(vector,int))= data.mapPartitions{
***
}.reduceByKey(***).collectAsMap()
sumsMap.foreach{case(index,(sum,count))=>
sum/=count
centers(index)=(sum,sum.norm2())
}
the origin codes are:
val centers = initCenters.getOrElse(initCenter(data))
val br_centers = data.sparkContext.broadcast(centers)
val trainData = data.map(e => (e._2, e._2.norm2)).cache()
val squareStopBound = stopBound * stopBound
var isConvergence = false
var i = 0
val costs = data.sparkContext.doubleAccumulator
while (!isConvergence && i < maxIters) {
costs.reset()
val res = trainData.mapPartitions { iter =>
val counts = new Array[Int](k)
util.Arrays.fill(counts, 0)
val partSum = (0 until k).map(e => new DenseVector(br_centers.value(0)._1.size))
iter.foreach { e =>
val (index, cost) = KMeans.findNearest(e, br_centers.value)
costs.add(cost)
counts(index) += 1
partSum(index) += e._1
}
counts.indices.filter(j => counts(j) > 0).map(j => (j -> (partSum(j), counts(j)))).iterator
}.reduceByKey { case ((s1, c1), (s2, c2)) =>
(s1 += s2, c1 + c2)
}.collectAsMap()
br_centers.unpersist(false)
println(s"cost at iter: $i is: ${costs.value}")
isConvergence = true
res.foreach { case (index, (sum, count)) =>
sum /= count
val sumNorm2 = sum.norm2()
val squareDist = math.pow(centers(index)._2, 2.0) + math.pow(sumNorm2, 2.0) - 2 * (centers(index)._1 * sum)
if (squareDist >= squareStopBound) {
isConvergence = false
}
centers.update(index,(sum, sumNorm2))
}
i += 1
}
when these run in a pseudo-distributed mode in IDEA, I get the centers updated, while when I get these run on a spark cluster, I do not get the centers updated.
LostInOverflow's answer is correct, but not especially descriptive as to what's going on.
Here are some important properties of your code:
declare an array centers
broadcast this array as br_centers
update centers iteratively
So how is this going wrong? Well, broadcasts are static. If I write:
val a = Array(1,2,3)
val aBc = sc.broadcast(a)
a(0) = 67
and access aBc.value(0), I'm going to get different results depending on whether this code was run on the driver JVM or not. Broadcasting takes an object, torrents it across the network to each node, and creates a new reference in each JVM. This reference exists as it did when the base object was broadcasted, and it is NOT updated in real time as you mutate the base object.
What's the solution? I think moving the broadcast inside the while loop so that you broadcast the updated centers should work:
while (!isConvergence && i < maxIters) {
val br_centers = data.sparkContext.broadcast(centers)
...
Please check Understanding closures section in the programming guide.
Spark is a distributed system and behavior of the code you've shown is simply undefined. It works in local mode only by accident because it executes everything in a single JVM.
I wrote a simple stream using akka-streams api assuming it will handle my source but unfortunately it doesn't. I am sure I am doing something wrong in my source. I simply created an iterator which generate very large number of elements assuming it won't matter because akka-streams api will take care of backpressure. What am I doing wrong, this is my iterator.
def createData(args: Array[String]): Iterator[TimeSeriesValue] = {
var data = new ListBuffer[TimeSeriesValue]()
for (i <- 1 to range) {
sessionId = UUID.randomUUID()
for (j <- 1 to countersPerSession) {
time = DateTime.now()
keyName = s"Encoder-${sessionId.toString}-Controller.CaptureFrameCount.$j"
for (k <- 1 to snapShotCount) {
time = time.plusSeconds(2)
fValue = new Random().nextLong()
data += TimeSeriesValue(sessionId, keyName, time, fValue)
totalRows += 1
}
}
}
data.iterator
}
The problem is primarily in the line
data += TimeSeriesValue(sessionId, keyName, time, fValue)
You are continuously adding to the ListBuffer with a "very large number of elements". This is chewing up all of your RAM. The data.iterator line is simply wrapping the massive ListBuffer blob inside of an iterator to provide each element one at a time, it's basically just a cast.
Your assumption that "it won't matter because ... of backpressure" is partially true that the akka Stream will process the TimeSeriesValue values reactively, but you are creating a large number of them even before you get to the Source constructor.
If you want this iterator to be "lazy", i.e. only produce values when needed and not consume memory, then make the following modifications (note: I broke apart the code to make it more readable):
def createTimeSeries(startTime: Time, snapShotCount : Int, sessionId : UUID, keyName : String) =
Iterator.range(1, snapShotCount)
.map(_ * 2)
.map(startTime plusSeconds _)
.map(t => TimeSeriesValue(sessionId, keyName, t, ThreadLocalRandom.current().nextLong()))
def sessionGenerator(countersPerSession : Int, sessionID : UUID) =
Iterator.range(1, countersPerSession)
.map(j => s"Encoder-${sessionId.toString}-Controller.CaptureFrameCount.$j")
.flatMap { keyName =>
createTimeSeries(DateTime.now(), snapShotCount, sessionID, keyName)
}
object UUIDIterator extends Iterator[UUID] {
def hasNext : Boolean = true
def next() : UUID = UUID.randomUUID()
}
def iterateOverIDs(range : Int) =
UUIDIterator.take(range)
.flatMap(sessionID => sessionGenerator(countersPerSession, sessionID))
Each one of the above functions returns an Iterator. Therefore, calling iterateOverIDs should be instantaneous because no work is immediately being done and de mimimis memory is being consumed. This iterator can then be passed into your Stream...
My Google Apps Script is iterating through the user's Google Drive files and copying and sometimes moving files to other folders. The script is always stopped after certain minutes with no error message in the log.
EDITOR's NOTE: The time limit have varied over the time and might vary between "consumer" (free) and "Workspace" (paid) accounts but as of December 2022 most of the answers are still valid.
I am sorting tens or sometimes thousands files in one run.
Are there any settings or workarounds?
One thing you could do (this of course depends on what you are trying to accomplish) is:
Store the necessary information (i.e. like a loop counter) in a spreadsheet or another permanent store(i.e. ScriptProperties).
Have your script terminate every five minutes or so.
Set up a time driven trigger to run the script every five minutes(or create a trigger programmatically using the Script service).
On each run read the saved data from the permanent store you've used and continue to run the script from where it left off.
This is not a one-size-fit-all solution, if you post your code people would be able to better assist you.
Here is a simplified code excerpt from a script that I use every day:
function runMe() {
var startTime= (new Date()).getTime();
//do some work here
var scriptProperties = PropertiesService.getScriptProperties();
var startRow= scriptProperties.getProperty('start_row');
for(var ii = startRow; ii <= size; ii++) {
var currTime = (new Date()).getTime();
if(currTime - startTime >= MAX_RUNNING_TIME) {
scriptProperties.setProperty("start_row", ii);
ScriptApp.newTrigger("runMe")
.timeBased()
.at(new Date(currTime+REASONABLE_TIME_TO_WAIT))
.create();
break;
} else {
doSomeWork();
}
}
//do some more work here
}
NOTE#1: The variable REASONABLE_TIME_TO_WAIT should be large enough for the new trigger to fire. (I set it to 5 minutes but I think it could be less than that).
NOTE#2: doSomeWork() must be a function that executes relatively quick( I would say less than 1 minute ).
NOTE#3 : Google has deprecated Script Properties, and introduced Properties Service in its stead. The function has been modified accordingly.
NOTE#4: 2nd time when the function is called, it takes the ith value of for loop as a string. so you have to convert it into an integer
Quotas
The maximum execution time for a single script is 6 mins / execution
- https://developers.google.com/apps-script/guides/services/quotas
But there are other limitations to familiarize yourself with. For example, you're only allowed a total trigger runtime of 1 hour / day, so you can't just break up a long function into 12 different 5 minute blocks.
Optimization
That said, there are very few reasons why you'd really need to take six minutes to execute. JavaScript should have no problem sorting thousands of rows of data in a couple seconds. What's likely hurting your performance are service calls to Google Apps itself.
You can write scripts to take maximum advantage of the built-in caching, by minimizing the number of reads and writes. Alternating read and write commands is slow. To speed up a script, read all data into an array with one command, perform any operations on the data in the array, and write the data out with one command.
- https://developers.google.com/apps-script/best_practices
Batching
The best thing you can possibly do is reduce the number of service calls. Google enables this by allowing batch versions of most of their API calls.
As a trivial example, Instead of this:
for (var i = 1; i <= 100; i++) {
SpreadsheetApp.getActiveSheet().deleteRow(i);
}
Do this:
SpreadsheetApp.getActiveSheet().deleteRows(i, 100);
In the first loop, not only did you need 100 calls to deleteRow on the sheet, but you also needed to get the active sheet 100 times as well. The second variation should perform several orders of magnitude better than the first.
Interweaving Reads and Writes
Additionally, you should also be very careful to not go back and forth frequently between reading and writing. Not only will you lose potential gains in batch operations, but Google won't be able to use its built-in caching.
Every time you do a read, we must first empty (commit) the write cache to ensure that you're reading the latest data (you can force a write of the cache by calling SpreadsheetApp.flush()). Likewise, every time you do a write, we have to throw away the read cache because it's no longer valid. Therefore if you can avoid interleaving reads and writes, you'll get full benefit of the cache.
- http://googleappsscript.blogspot.com/2010/06/optimizing-spreadsheet-operations.html
For example, instead of this:
sheet.getRange("A1").setValue(1);
sheet.getRange("B1").setValue(2);
sheet.getRange("C1").setValue(3);
sheet.getRange("D1").setValue(4);
Do this:
sheet.getRange("A1:D1").setValues([[1,2,3,4]]);
Chaining Function Calls
As a last resort, if your function really can't finish in under six minutes, you can chain together calls or break up your function to work on a smaller segment of data.
You can store data in the Cache Service (temporary) or Properties Service (permanent) buckets for retrieval across executions (since Google Apps Scripts has a stateless execution).
If you want to kick off another event, you can create your own trigger with the Trigger Builder Class or setup a recurring trigger on a tight time table.
Also, try to minimize the amount of calls to google services. For example, if you want to change a range of cells in the spreadsheets, don't read each one, mutate it and store it back.
Instead read the whole range (using Range.getValues()) into memory, mutate it and store all of it at once (using Range.setValues()).
This should save you a lot of execution time.
Anton Soradoi's answer seems OK but consider using Cache Service instead of storing data into a temporary sheet.
function getRssFeed() {
var cache = CacheService.getPublicCache();
var cached = cache.get("rss-feed-contents");
if (cached != null) {
return cached;
}
var result = UrlFetchApp.fetch("http://example.com/my-slow-rss-feed.xml"); // takes 20 seconds
var contents = result.getContentText();
cache.put("rss-feed-contents", contents, 1500); // cache for 25 minutes
return contents;
}
Also note that as of April 2014 the limitation of script runtime is 6 minutes.
G Suite Business / Enterprise / Education and Early Access users:
As of August 2018, max script runtime is now set to 30 minutes for these users.
Figure out a way to split up your work so it takes less than 6 minutes, as that's the limit for any script. On the first pass, you can iterate and store the list of files and folders in a spreadsheet and add a time-driven trigger for part 2.
In part 2, delete each entry in the list as you process it. When there are no items in the list, delete the trigger.
This is how I'm processing a sheet of about 1500 rows that gets spread to about a dozen different spreadsheets. Because of the number of calls to spreadsheets, it times out, but continues when the trigger runs again.
I have used the ScriptDB to save my place while processing a large amount of information in a loop. The script can/does exceed the 5 minute limit. By updating the ScriptDb during each run, the script can read the state from the db and pick up where it left off until all processing is complete. Give this strategy a try and I think you'll be pleased with the results.
If you are using G Suite Business or Enterprise edition.
You can register early access for App Maker after App maker enabled your script run runtime will increase run time from 6 minutes to 30 minutes :)
More details about app maker Click here
Here's an approach based very heavily on Dmitry Kostyuk's absolutely excellent article on the subject.
It differs in that it doesn't attempt to time execution and exit gracefully. Rather, it deliberately spawns a new thread every minute, and lets them run until they are timed out by Google. This gets round the maximum execution time limit, and speeds things up by running processing in several threads in parallel. (This speeds things up even if you are not hitting execution time limits.)
It tracks the task status in script properties, plus a semaphore to ensure no two threads are editing the task status at any one time. (It uses several properties as they are limited to 9k each.)
I have tried to mimick the Google Apps Script iterator.next() API, but cannot use iterator.hasNext() as that would not be thread-safe (see TOCTOU). It uses a couple of facade classes at the bottom.
I would be immensely grateful for any suggestions. This is working well for me, halving the processing time by spawning three parallel threads to run through a directory of documents. You could spawn 20 within quota, but this was ample for my use case.
The class is designed to be drop-in, usable for any purpose without modification. The only thing the user must do is when processing a file, delete any outputs from prior, timed out attempts. The iterator will return a given fileId more than once if a processing task is timed out by Google before it completes.
To silence the logging, it all goes through the log() function at the bottom.
This is how you use it:
const main = () => {
const srcFolder = DriveApp.getFoldersByName('source folder',).next()
const processingMessage = processDocuments(srcFolder, 'spawnConverter')
log('main() finished with message', processingMessage)
}
const spawnConverter = e => {
const processingMessage = processDocuments()
log('spawnConverter() finished with message', processingMessage)
}
const processDocuments = (folder = null, spawnFunction = null) => {
// folder and spawnFunction are only passed the first time we trigger this function,
// threads spawned by triggers pass nothing.
// 10,000 is the maximum number of milliseconds a file can take to process.
const pfi = new ParallelFileIterator(10000, MimeType.GOOGLE_DOCS, folder, spawnFunction)
let fileId = pfi.nextId()
const doneDocs = []
while (fileId) {
const fileRelativePath = pfi.getFileRelativePath(fileId)
const doc = DocumentApp.openById(fileId)
const mc = MarkupConverter(doc)
// This is my time-consuming task:
const mdContent = mc.asMarkdown(doc)
pfi.completed(fileId)
doneDocs.push([...fileRelativePath, doc.getName() + '.md'].join('/'))
fileId = pfi.nextId()
}
return ('This thread did:\r' + doneDocs.join('\r'))
}
Here's the code:
const ParallelFileIterator = (function() {
/**
* Scans a folder, depth first, and returns a file at a time of the given mimeType.
* Uses ScriptProperties so that this class can be used to process files by many threads in parallel.
* It is the responsibility of the caller to tidy up artifacts left behind by processing threads that were timed out before completion.
* This class will repeatedly dispatch a file until .completed(fileId) is called.
* It will wait maxDurationOneFileMs before re-dispatching a file.
* Note that Google Apps kills scripts after 6 mins, or 30 mins if you're using a Workspace account, or 45 seconds for a simple trigger, and permits max 30
* scripts in parallel, 20 triggers per script, and 90 mins or 6hrs of total trigger runtime depending if you're using a Workspace account.
* Ref: https://developers.google.com/apps-script/guides/services/quotas
maxDurationOneFileMs, mimeType, parentFolder=null, spawnFunction=null
* #param {Number} maxDurationOneFileMs A generous estimate of the longest a file can take to process.
* #param {string} mimeType The mimeType of the files required.
* #param {Folder} parentFolder The top folder containing all the files to process. Only passed in by the first thread. Later spawned threads pass null (the files have already been listed and stored in properties).
* #param {string} spawnFunction The name of the function that will spawn new processing threads. Only passed in by the first thread. Later spawned threads pass null (a trigger can't create a trigger).
*/
class ParallelFileIterator {
constructor(
maxDurationOneFileMs,
mimeType,
parentFolder = null,
spawnFunction = null,
) {
log(
'Enter ParallelFileIterator constructor',
maxDurationOneFileMs,
mimeType,
spawnFunction,
parentFolder ? parentFolder.getName() : null,
)
// singleton
if (ParallelFileIterator.instance) return ParallelFileIterator.instance
if (parentFolder) {
_cleanUp()
const t0 = Now.asTimestamp()
_getPropsLock(maxDurationOneFileMs)
const t1 = Now.asTimestamp()
const { fileIds, fileRelativePaths } = _catalogFiles(
parentFolder,
mimeType,
)
const t2 = Now.asTimestamp()
_setQueues(fileIds, [])
const t3 = Now.asTimestamp()
this.fileRelativePaths = fileRelativePaths
ScriptProps.setAsJson(_propsKeyFileRelativePaths, fileRelativePaths)
const t4 = Now.asTimestamp()
_releasePropsLock()
const t5 = Now.asTimestamp()
if (spawnFunction) {
// only triggered on the first thread
const trigger = Trigger.create(spawnFunction, 1)
log(
`Trigger once per minute: UniqueId: ${trigger.getUniqueId()}, EventType: ${trigger.getEventType()}, HandlerFunction: ${trigger.getHandlerFunction()}, TriggerSource: ${trigger.getTriggerSource()}, TriggerSourceId: ${trigger.getTriggerSourceId()}.`,
)
}
log(
`PFI instantiated for the first time, has found ${
fileIds.length
} documents to process. getPropsLock took ${t1 -
t0}ms, _catalogFiles took ${t2 - t1}ms, setQueues took ${t3 -
t2}ms, setAsJson took ${t4 - t3}ms, releasePropsLock took ${t5 -
t4}ms, trigger creation took ${Now.asTimestamp() - t5}ms.`,
)
} else {
const t0 = Now.asTimestamp()
// wait for first thread to set up Properties
while (!ScriptProps.getJson(_propsKeyFileRelativePaths)) {
Utilities.sleep(250)
}
this.fileRelativePaths = ScriptProps.getJson(_propsKeyFileRelativePaths)
const t1 = Now.asTimestamp()
log(
`PFI instantiated again to run in parallel. getJson(paths) took ${t1 -
t0}ms`,
)
spawnFunction
}
_internals.set(this, { maxDurationOneFileMs: maxDurationOneFileMs })
// to get: _internal(this, 'maxDurationOneFileMs')
ParallelFileIterator.instance = this
return ParallelFileIterator.instance
}
nextId() {
// returns false if there are no more documents
const maxDurationOneFileMs = _internals.get(this).maxDurationOneFileMs
_getPropsLock(maxDurationOneFileMs)
let { pending, dispatched } = _getQueues()
log(
`PFI.nextId: ${pending.length} files pending, ${
dispatched.length
} dispatched, ${Object.keys(this.fileRelativePaths).length -
pending.length -
dispatched.length} completed.`,
)
if (pending.length) {
// get first pending Id, (ie, deepest first)
const nextId = pending.shift()
dispatched.push([nextId, Now.asTimestamp()])
_setQueues(pending, dispatched)
_releasePropsLock()
return nextId
} else if (dispatched.length) {
log(`PFI.nextId: Get first dispatched Id, (ie, oldest first)`)
let startTime = dispatched[0][1]
let timeToTimeout = startTime + maxDurationOneFileMs - Now.asTimestamp()
while (dispatched.length && timeToTimeout > 0) {
log(
`PFI.nextId: None are pending, and the oldest dispatched one hasn't yet timed out, so wait ${timeToTimeout}ms to see if it will`,
)
_releasePropsLock()
Utilities.sleep(timeToTimeout + 500)
_getPropsLock(maxDurationOneFileMs)
;({ pending, dispatched } = _getQueues())
if (pending && dispatched) {
if (dispatched.length) {
startTime = dispatched[0][1]
timeToTimeout =
startTime + maxDurationOneFileMs - Now.asTimestamp()
}
}
}
// We currently still have the PropsLock
if (dispatched.length) {
const nextId = dispatched.shift()[0]
log(
`PFI.nextId: Document id ${nextId} has timed out; reset start time, move to back of queue, and re-dispatch`,
)
dispatched.push([nextId, Now.asTimestamp()])
_setQueues(pending, dispatched)
_releasePropsLock()
return nextId
}
}
log(`PFI.nextId: Both queues empty, all done!`)
;({ pending, dispatched } = _getQueues())
if (pending.length || dispatched.length) {
log(
"ERROR: All documents should be completed, but they're not. Giving up.",
pending,
dispatched,
)
}
_cleanUp()
return false
}
completed(fileId) {
_getPropsLock(_internals.get(this).maxDurationOneFileMs)
const { pending, dispatched } = _getQueues()
const newDispatched = dispatched.filter(el => el[0] !== fileId)
if (dispatched.length !== newDispatched.length + 1) {
log(
'ERROR: A document was completed, but not found in the dispatched list.',
fileId,
pending,
dispatched,
)
}
if (pending.length || newDispatched.length) {
_setQueues(pending, newDispatched)
_releasePropsLock()
} else {
log(`PFI.completed: Both queues empty, all done!`)
_cleanUp()
}
}
getFileRelativePath(fileId) {
return this.fileRelativePaths[fileId]
}
}
// ============= PRIVATE MEMBERS ============= //
const _propsKeyLock = 'PropertiesLock'
const _propsKeyDispatched = 'Dispatched'
const _propsKeyPending = 'Pending'
const _propsKeyFileRelativePaths = 'FileRelativePaths'
// Not really necessary for a singleton, but in case code is changed later
var _internals = new WeakMap()
const _cleanUp = (exceptProp = null) => {
log('Enter _cleanUp', exceptProp)
Trigger.deleteAll()
if (exceptProp) {
ScriptProps.deleteAllExcept(exceptProp)
} else {
ScriptProps.deleteAll()
}
}
const _catalogFiles = (folder, mimeType, relativePath = []) => {
// returns IDs of all matching files in folder, depth first
log(
'Enter _catalogFiles',
folder.getName(),
mimeType,
relativePath.join('/'),
)
let fileIds = []
let fileRelativePaths = {}
const folders = folder.getFolders()
let subFolder
while (folders.hasNext()) {
subFolder = folders.next()
const results = _catalogFiles(subFolder, mimeType, [
...relativePath,
subFolder.getName(),
])
fileIds = fileIds.concat(results.fileIds)
fileRelativePaths = { ...fileRelativePaths, ...results.fileRelativePaths }
}
const files = folder.getFilesByType(mimeType)
while (files.hasNext()) {
const fileId = files.next().getId()
fileIds.push(fileId)
fileRelativePaths[fileId] = relativePath
}
return { fileIds: fileIds, fileRelativePaths: fileRelativePaths }
}
const _getQueues = () => {
const pending = ScriptProps.getJson(_propsKeyPending)
const dispatched = ScriptProps.getJson(_propsKeyDispatched)
log('Exit _getQueues', pending, dispatched)
// Note: Empty lists in Javascript are truthy, but if Properties have been deleted by another thread they'll be null here, which are falsey
return { pending: pending || [], dispatched: dispatched || [] }
}
const _setQueues = (pending, dispatched) => {
log('Enter _setQueues', pending, dispatched)
ScriptProps.setAsJson(_propsKeyPending, pending)
ScriptProps.setAsJson(_propsKeyDispatched, dispatched)
}
const _getPropsLock = maxDurationOneFileMs => {
// will block until lock available or lock times out (because a script may be killed while holding a lock)
const t0 = Now.asTimestamp()
while (
ScriptProps.getNum(_propsKeyLock) + maxDurationOneFileMs >
Now.asTimestamp()
) {
Utilities.sleep(2000)
}
ScriptProps.set(_propsKeyLock, Now.asTimestamp())
log(`Exit _getPropsLock: took ${Now.asTimestamp() - t0}ms`)
}
const _releasePropsLock = () => {
ScriptProps.delete(_propsKeyLock)
log('Exit _releasePropsLock')
}
return ParallelFileIterator
})()
const log = (...args) => {
// easier to turn off, json harder to read but easier to hack with
console.log(args.map(arg => JSON.stringify(arg)).join(';'))
}
class Trigger {
// Script triggering facade
static create(functionName, everyMinutes) {
return ScriptApp.newTrigger(functionName)
.timeBased()
.everyMinutes(everyMinutes)
.create()
}
static delete(e) {
if (typeof e !== 'object') return log(`${e} is not an event object`)
if (!e.triggerUid)
return log(`${JSON.stringify(e)} doesn't have a triggerUid`)
ScriptApp.getProjectTriggers().forEach(trigger => {
if (trigger.getUniqueId() === e.triggerUid) {
log('deleting trigger', e.triggerUid)
return ScriptApp.delete(trigger)
}
})
}
static deleteAll() {
// Deletes all triggers in the current project.
var triggers = ScriptApp.getProjectTriggers()
for (var i = 0; i < triggers.length; i++) {
ScriptApp.deleteTrigger(triggers[i])
}
}
}
class ScriptProps {
// properties facade
static set(key, value) {
if (value === null || value === undefined) {
ScriptProps.delete(key)
} else {
PropertiesService.getScriptProperties().setProperty(key, value)
}
}
static getStr(key) {
return PropertiesService.getScriptProperties().getProperty(key)
}
static getNum(key) {
// missing key returns Number(null), ie, 0
return Number(ScriptProps.getStr(key))
}
static setAsJson(key, value) {
return ScriptProps.set(key, JSON.stringify(value))
}
static getJson(key) {
return JSON.parse(ScriptProps.getStr(key))
}
static delete(key) {
PropertiesService.getScriptProperties().deleteProperty(key)
}
static deleteAll() {
PropertiesService.getScriptProperties().deleteAllProperties()
}
static deleteAllExcept(key) {
PropertiesService.getScriptProperties()
.getKeys()
.forEach(curKey => {
if (curKey !== key) ScriptProps.delete(key)
})
}
}
If you're a business customer, you can now sign up for Early Access to App Maker, which includes Flexible Quotas.
Under the flexible quota system, such hard quota limits are removed. Scripts do not stop when they reach a quota limit. Rather, they are delayed until quota becomes available, at which point the script execution resumes. Once quotas begin being used, they are refilled at a regular rate. For reasonable usage, script delays are rare.
If you are using G Suite as a Business, Enterprise or EDU customer the execution time for running scripts is set to:
30 min / execution
See: https://developers.google.com/apps-script/guides/services/quotas
The idea would be to exit gracefully from the script, save your progress, create a trigger to start again from where you left off, repeat as many times as necessary and then once finished clean up the trigger and any temporary files.
Here is a detailed article on this very topic.
As many people mentioned, the generic solution to this problem is to execute your method across multiple sessions. I found it to be a common problem that I have a bunch of iterations I need to loop over, and I don't want the hassle of writing/maintaining the boilerplate of creating new sessions.
Therefore I created a general solution:
/**
* Executes the given function across multiple sessions to ensure there are no timeouts.
*
* See https://stackoverflow.com/a/71089403.
*
* #param {Int} items - The items to iterate over.
* #param {function(Int)} fn - The function to execute each time. Takes in an item from `items`.
* #param {String} resumeFunctionName - The name of the function (without arguments) to run between sessions. Typically this is the same name of the function that called this method.
* #param {Int} maxRunningTimeInSecs - The maximum number of seconds a script should be able to run. After this amount, it will start a new session. Note: This must be set to less than the actual timeout as defined in https://developers.google.com/apps-script/guides/services/quotas (e.g. 6 minutes), otherwise it can't set up the next call.
* #param {Int} timeBetweenIterationsInSeconds - The amount of time between iterations of sessions. Note that Google Apps Script won't honor this 100%, as if you choose a 1 second delay, it may actually take a minute or two before it actually executes.
*/
function iterateAcrossSessions(items, fn, resumeFunctionName, maxRunningTimeInSeconds = 5 * 60, timeBetweenIterationsInSeconds = 1) {
const PROPERTY_NAME = 'iterateAcrossSessions_index';
let scriptProperties = PropertiesService.getScriptProperties();
let startTime = (new Date()).getTime();
let startIndex = parseInt(scriptProperties.getProperty(PROPERTY_NAME));
if (Number.isNaN(startIndex)) {
startIndex = 0;
}
for (let i = startIndex; i < items.length; i++) {
console.info(`[iterateAcrossSessions] Executing for i = ${i}.`)
fn(items[i]);
let currentTime = (new Date()).getTime();
let elapsedTime = currentTime - startTime;
let maxRunningTimeInMilliseconds = maxRunningTimeInSeconds * 1000;
if (maxRunningTimeInMilliseconds <= elapsedTime) {
let newTime = new Date(currentTime + timeBetweenIterationsInSeconds * 1000);
console.info(`[iterateAcrossSessions] Creating new session for i = ${i+1} at ${newTime}, since elapsed time was ${elapsedTime}.`);
scriptProperties.setProperty(PROPERTY_NAME, i+1);
ScriptApp.newTrigger(resumeFunctionName).timeBased().at(newTime).create();
return;
}
}
console.log(`[iterateAcrossSessions] Done iterating over items.`);
// Reset the property here to ensure that the execution loop could be restarted.
scriptProperties.deleteProperty(PROPERTY_NAME);
}
You can now use this pretty easily like so:
let ITEMS = ['A', 'B', 'C'];
function execute() {
iterateAcrossSessions(
ITEMS,
(item) => {
console.log(`Hello world ${item}`);
},
"execute");
}
It'll automatically execute the internal lambda for each value in ITEMS, seamlessly spreading across sessions as needed.
For example, if you use a 0-second maxRunningTime it would run across 4 sessions with the following outputs:
[iterateAcrossSessions] Executing for i = 0.
Hello world A
[iterateAcrossSessions] Creating new session for i = 1.
[iterateAcrossSessions] Executing for i = 1.
Hello world B
[iterateAcrossSessions] Creating new session for i = 2.
[iterateAcrossSessions] Executing for i = 2.
Hello world C
[iterateAcrossSessions] Creating new session for i = 3.
[iterateAcrossSessions] Done iterating over items.
I am new to SalesForce (3 months).
Thus far I have been able to create an application in C# that I can use to preform Inserts and Updates to the SalesForce database. These transactions are one at a time.
No I have the need to preform large scale transactions. For example updating thousands of records at a time. Doing them one by one would quickly put us over our allotted API calls per 24 hour period.
I want to utilize the available bulk transactions process to cut down on the number of API calls. Thus far I have not had much luck coding this nor have I found any such documentation.
If anyone could either provide some generic examples or steer me to reliable documentation on the subject I would greatly appreciate it.
FYI, the data I need to use to do the updates and inserts comes from an IBM Unidata database sitting on an AIX machine. So direct web services communication is not realy possible. Getting the data from Unidata has been my headache. I have that worked out. Now the bulk api to SalesForce is my new headache.
Thanks in advance.
Jeff
You don't mention which API you're currently using, but using the soap partner or enterprise APIs you can write records to salesforce 200 at a time. (the create/update/upsert calls all take an array of SObjects).
Using the bulk API you can send data in chunks of thousands of rows at a time.
You can find the documentation for both sets of APIs here
The answers already given are a good start; however, are you sure you need to actually write a custom app that uses the bulk API? The salesforce data loader is a pretty robust tool, includes a command line interface, and can use either the "normal" or bulk data API's. Unless you are needing to do fancy logic as part of your insert/updates, or some sort of more real-time / on-demand loading, the data loader is going to be a better option than a custom app.
(this is the SOAP code though, not the Salesforce "Bulk API" ; careful not to confuse the two)
Mighy be below code provide clear insight on how to do bulk insertion.
/// Demonstrates how to create one or more Account records via the API
public void CreateAccountSample()
{
Account account1 = new Account();
Account account2 = new Account();
// Set some fields on the account1 object. Name field is not set
// so this record should fail as it is a required field.
account1.BillingCity = "Wichita";
account1.BillingCountry = "US";
account1.BillingState = "KA";
account1.BillingStreet = "4322 Haystack Boulevard";
account1.BillingPostalCode = "87901";
// Set some fields on the account2 object
account2.Name = "Golden Straw";
account2.BillingCity = "Oakland";
account2.BillingCountry = "US";
account2.BillingState = "CA";
account2.BillingStreet = "666 Raiders Boulevard";
account2.BillingPostalCode = "97502";
// Create an array of SObjects to hold the accounts
sObject[] accounts = new sObject[2];
// Add the accounts to the SObject array
accounts[0] = account1;
accounts[1] = account2;
// Invoke the create() call
try
{
SaveResult[] saveResults = binding.create(accounts);
// Handle the results
for (int i = 0; i < saveResults.Length; i++)
{
// Determine whether create() succeeded or had errors
if (saveResults[i].success)
{
// No errors, so retrieve the Id created for this record
Console.WriteLine("An Account was created with Id: {0}",
saveResults[i].id);
}
else
{
Console.WriteLine("Item {0} had an error updating", i);
// Handle the errors
foreach (Error error in saveResults[i].errors)
{
Console.WriteLine("Error code is: {0}",
error.statusCode.ToString());
Console.WriteLine("Error message: {0}", error.message);
}
}
}
}
catch (SoapException e)
{
Console.WriteLine(e.Code);
Console.WriteLine(e.Message);
}
}
Please find the small code which may help you to insert the data into salesforce objects using c# and WSDL APIs. I stuck to much to write code in c#. I assigned using direct index after spiting you can use your ways.
I split the column using | (pipe sign). You may change this and also <br>, \n, etc. (row and column breaking)
Means you can enter N rows which are in your HTML/text file. I wrote the program to add order by my designers who put the order on other website and fetch the data from e-commerce website and who has no interface for the salesforce to add/view the order records. I created one object for the same. and add following columns in the object.
Your suggestions are welcome.
private SforceService binding; // declare the salesforce servive using your access credential
try
{
string stroppid = "111111111111111111";
System.Net.HttpWebRequest fr;
Uri targetUri = new Uri("http://abc.xyz.com/test.html");
fr = (System.Net.HttpWebRequest)System.Net.HttpWebRequest.Create(targetUri);
if ((fr.GetResponse().ContentLength > 0))
{
System.IO.StreamReader str = new System.IO.StreamReader(fr.GetResponse().GetResponseStream());
string allrow = str.ReadToEnd();
string stringSeparators = "<br>";
string[] row1 = Regex.Split(allrow, stringSeparators);
CDI_Order_Data__c[] cord = new CDI_Order_Data__c[row1.Length - 1];
for (int i = 1; i < row1.Length-1; i++)
{
string colstr = row1[i].ToString();
string[] allcols = Regex.Split(colstr, "\\|");
cord[i] = new CDI_Order_Data__c(); // Very important to create object
cord[i].Opportunity_Job_Order__c = stroppid;
cord[i].jobid__c = stroppid;
cord[i].order__c = allcols[0].ToString();
cord[i].firstname__c = allcols[1].ToString();
cord[i].name__c = allcols[2].ToString();
DateTime dtDate = Convert.ToDateTime(allcols[3]);
cord[i].Date__c = new DateTime(Convert.ToInt32(dtDate.Year), Convert.ToInt32(dtDate.Month), Convert.ToInt32(dtDate.Day), 0, 0, 0); //sforcedate(allcols[3]); //XMLstringToDate(allcols[3]);
cord[i].clientpo__c = allcols[4].ToString();
cord[i].billaddr1__c = allcols[5].ToString();
cord[i].billaddr2__c = allcols[6].ToString();
cord[i].billcity__c = allcols[7].ToString();
cord[i].billstate__c = allcols[8].ToString();
cord[i].billzip__c = allcols[9].ToString();
cord[i].phone__c = allcols[10].ToString();
cord[i].fax__c = allcols[11].ToString();
cord[i].email__c = allcols[12].ToString();
cord[i].contact__c = allcols[13].ToString();
cord[i].lastname__c = allcols[15].ToString();
cord[i].Rep__c = allcols[16].ToString();
cord[i].sidemark__c = allcols[17].ToString();
cord[i].account__c = allcols[18].ToString();
cord[i].item__c = allcols[19].ToString();
cord[i].kmatid__c = allcols[20].ToString();
cord[i].qty__c = Convert.ToDouble(allcols[21]);
cord[i].Description__c = allcols[22].ToString();
cord[i].price__c = Convert.ToDouble(allcols[23]);
cord[i].installation__c = allcols[24].ToString();
cord[i].freight__c = allcols[25].ToString();
cord[i].discount__c = Convert.ToDouble(allcols[26]);
cord[i].salestax__c = Convert.ToDouble(allcols[27]);
cord[i].taxcode__c = allcols[28].ToString();
}
try {
SaveResult[] saveResults = binding.create(cord);
}
catch (Exception ce)
{
Response.Write("Buld order update errror" +ce.Message.ToString());
Response.End();
}
if (str != null) str.Close();
}